Abrahams, S. (2020). Officer differences in traffic stops of minority drivers. Labour Economics, 67, 101912. 

Ahani, A., Mousavi Nadoushani, S. S., & Moridi, A. (2020). Regionalization of watersheds by finite mixture models. Journal of Hydrology, 583, 124620. 

Ahmed, A. O. M., Al-Kutubi, H. S., & Ibrahim, N. A. (2010). Comparison of the bayesian and maximum likelihood estimation for Weibull distribution. Journal of Mathematics and Statistics, 6(2), 100–104. 

Aho, A. V., & Peterson, T. G. (1972). A minimum distance error-correcting parser for context-free languages. SIAM Journal on Computing, 1(4), 305–312. 

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. 

Alamri, O. A., Abd El-Raouf, M. M., Ismail,E. A., Almaspoor, Z., Alsaedi, B. S. O., Khosa, S. A., & Yusuf, M. (2021). Estimate stress-strength reliability model using Rayleigh and half-normal distribution. Computational Intelligence 

and Neuroscience, Special Issue, 7653581. 

Almasi-Hashiani, A., Nedjat, S., Ghiasvand, R., Safiri, S., Nazemipour, M., Mansournia, N., et al. (2021). The causal effect and impact of reproductive factors on breast cancer using super learner and targeted maximum likelihood estimation: a case-control study in Fars Province, Iran. BMC Public Health, 21(1), 1219. 

Al-Moisheer, A. S., Daghestani, A. F., & Sultan, K. S. (2020). Mixture of two one-parameter Lindley distributions: properties and estimation. Journal of Statistical Theory and Practice, 15(1). 

Alston, C. L., & Mengersen, K. L. (2010). Allowing for the effect of data binning in a Bayesian normal mixture model. Computational Statistics & Data Analysis, 54(4), 916–923. 

Alvi, M. A., & Rafique, A. (2020). Bank competition and stability relationship: evidence from selected south Asian economies. International Transaction Journal of Engineering Management & Applied Sciences & Technologies, 11(9), 11A9H 

An, D., Choi, J. H., Kim, N. H., & Pattabhiraman, S. (2011). Fatigue life prediction based on Bayesian approach to incorporate field data into probability model. Structural Engineering and Mechanics, 37(4), 427–442. 

Andrade, M. G., & Oliveira, S. C. (2011). A comparative study of Bayesian and maximum likelihood approaches for arch models with evidence from Brazilian financial series. New Mathematics and Natural Computation, 7(2), 347–361. 

Ardianti, F., & Sutarman. (2018). Estimating parameter of Rayleigh distribution by using maximum likelihood method and Bayes method. In IOP Conference Series: Materials Science and Engineering, 300, 012036. 

Arltová, M., & Fedorová,D. (2016).Selection of unitroot test on the basisof length of the time series and value of AR(1) parameter. Statistika, 96(3), 47–64. 

Arshad, F. M., & Radam, A. (1997). Export performance of selected electrical and electronicproducts. In: Towards ManagementExcellencein21stCentury Asia, Proceedings of the Second Asian Academy of Management Conference in Langkawi, Malaysia, 12-13 December, 1–22. 

ASEAN. (n.d.). Electronics: where to invest? [Online], [Accessed 14thAugust 2020]. Retrieved from http://investasean.asean.org/index.php/page/view/electronics 

Asian Development Bank. (2009, April). The global economic crisis: challenges for developing Asia and ADB’s response. Retrieved from https:// www.adb.org/ sites/default/files/publication/29705/global-economic-crisis-adb-response.pdf 

Asian Development Bank. (2011, September 14). ADB trims 2011 Philippine growth forecast on subdued state spending, exports. Retrieved from https://www.adb.org/ news/adb-trims-2011-philippine-growth-forecast­subdued-state-spending-exports 

Assouto, A. B., Houensou, D. A., & Semedo, G. (2020). Price risk and farmers' decisions: A case study from Benin. Scientific African, 8, e00311. 

Atrashkevich, V. V., Garanin, A. V., & Kolotov, V. P. (1987). Themethodof moments for multiplet deconvolution in gamma-ray spectrometry. Analytica Chimica Acta, 203(1), 43–54. 

Avdis, E., & Wachter, J. A. (2017). Maximum likelihood estimation of the equity premium. Journal of Financial Economics, 125(3), 589–609. 

Ayodeji, I. O. (2016). A three-state Markov-Modulated switching model for exchange rates. Journal of Applied Mathematics. doi: 10.1155/2016/5061749 

Balestra, C., Boarini, R., & Tosetto, E. (2018). What matters most to people? evidence from the OECD better life index users' responses. Social Indicators Research, 136 (3), 907–930. 

Bank Negara Malaysia. (2006, March 21). Bank negara Malaysia annual report 2005. Retrieved from https://www.bnm.gov.my/documents/20124/830659/ar2005_ book.pdf 

Bank Negara Malaysia. (2007, March 22). Bank negara Malaysia annual report 2006. Retrieved from https://www.bnm.gov.my/documents/20124/830610/ar2006_ book.pdf 

Bank NegaraMalaysia. (2009). Bank Negara Malaysia Annual Report 2008.Retrieved from https://www.bnm.gov.my/documents/20124/830490/ar2008book.pdf 

Bank Negara Malaysia. (2016, March 23). Bank negara Malaysia annual report 2015. Retrieved from https://www.bnm.gov.my/documents/20124/829207/annex.pdf 

Bank NegaraMalaysia. (2017). Bank Negara Malaysia Annual Report 2016. Retrieved from https://www.bnm.gov.my/documents/20124/829203/ar2016_ book.pdf 

Bank NegaraMalaysia. (2019a, March 27).Bank negara Malaysia annual report 2018. Retrieved from https://www.bnm.gov.my/files/publication/ar/en/2018/cp01.pdf 

Bank Negara Malaysia. (2019b, Nov 15). Economic and financial developments in Malaysian economy in the third quarter of 2019. Retrieved from https://www.bnm.gov.my/files/publication/qb/2019/Q3/p3.pdf 

Bank Negara Malaysia. (2021). Economic and monetary review 2020. Retrieved from https://www.bnm.gov.my/documents/20124/3026377/emr2020_en_book.pdf 

Bank of Thailand. (2006, March). Thailand’s economic and monetary conditions in 2005. Retrieved from https://www.bot.or.th/English/MonetaryPolicy/ EconomicConditions /AnnualReport/ AnnualReport/AnnualReport_2004.pdf 

Bank of Thailand. (2015). Thailand’s economic conditions in 2014. Retrieved from https://www.bot.or.th/English/MonetaryPolicy/EconomicConditions/AnnualReport/AnnualReport/Annual_eng_2014.pdf 

Bank of Thailand. (2016). Thailand’s economic conditions in 2015. Retrieved from https://www.bot.or.th/English/MonetaryPolicy/EconomicConditions/AnnualReport/AnnualReport/annual2015_V2.pdf 

Bank of Thailand. (2017). Thailand’s economic conditions in 2016. Retrieved from https://www.bot.or.th/English/MonetaryPolicy/EconomicConditions/AnnualReport/AnnualReport/annual_2016_V2.pdf 

Batalla, E. V. C. (2016). Divided politics and economic growth in the Philippines. Journal of Current Southeast Asian Affairs, 35(3), 161–186. 

Batten, D. S., & Thornton, D. L. (1985). The discount rate, interest rates and foreign exchange rates: an analysis with daily data. Federal Reserve Bank of St. Louis Review, 22–30. 

Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society, 53, 370–418. 

Beerli, P. (2005). Comparison of Bayesian and maximum-likelihood inference of population genetic parameters. Bioinformatics, 22(3), 341–345. 

Berg, V. D. H., & Lewer, J. J. (2015). International trade and economic growth. New York: Routledge. 

Bicer, B. M. (2020). A novel coplanar waveguide-fed compact microstrip antenna for future 5g applications. Tehnicki Glasnik-Technical Journal, 14(2), 104–110. 

Bernardi, M., Maruotti, A., & Petrella, L. (2012). Skew mixture models for loss distributions: A Bayesian approach. Insurance: Mathematics and Economics, 51(3), 617–623. 

Bernardo, J. M. (2001). Bayesian statistics. In: Encyclopedia of Life Support Systems. UNESCO. Retrieved from https://www.uv.es/bernardo/BayesStat.pdf 

Boa, I., Johnson, P., & King, S. (2010). The impact of research on the policy process.Working Paper No 82. 

Bogdan, Z., Cota, B., & Erjavec, N. (2017). Current account balance and export performances: Evidence based on new EU countries. Zagred International Review of Economics & Business, 20(2), 33–48. 

Box, G. E. P., & Tiao, G. C. (1973). Bayesian Inference in Statistical Analysis. John Wiley & Sons. 

Bresler, E., & Naor, A. (1987). Estimating transport parameters in soils byamaximum likelihood approach. Soil Science Society of America, 57, 870–875. 

Bui, T. N. (2020). How does the relationship between economic growth and bank efficiency? evidence from ASEAN countries. International Transaction Journal of Engineering Management & Applied Sciences & Technologies, 11(7),11A07F 

Bunday, B. D., & Al-Ayoubi, I. D. (1990). Likelihood and Bayesian estimation methods for Poisson process models in software reliability. International Journal of Quality & Reliability Management, 7(5), 9–18. 

Carvalho, M., Azevedo, A., & Massuquetti, A. (2019). Emerging countries and the effects of the trade war between US and China. Economies, Multidisciplinary Digital Publishing Institute, 7(2), 1–21. 

Case, W. (2017). Stress testing leadership in Malaysia: the 1MDB scandal and Najib Tun Razak. The Pacific Review, 30(5), 633–654. 

Cavanaugh, J. E., & Neath, A. A. (2019). The Akaike information criterion: background, derivation, properties, application, interpretation, and refinements. Wiley Interdisciplinary Reviews: Computational Statistics, e1460. 

Central Bank ofthePhilippines. (2020). BSP unbound: central banking and the covid­19 pandemic in the Philippines.Manila: BangkoSentral Ng Pilipinas. 

Chaito, T., Nanthaprut, P., Nakharutai, N., & Khamkong, M. (2022). Thelength-biased gamma-Rayleigh distribution with applications. Thailand Statistician, 20 (2), 293–307. 

Chakrabarti, A., & Ghosh, J. K. (2011). AIC, BIC and recent advances in model selection. Philosophy of Statistics, 583–605. 

Chao, Z. H., Komatsu, R., Woo, H., Tamura, Y., Yamashita, A., & Asama, H. (2022). Radiation distribution estimation with a non-directional detector using a plane source model*. Advanced Robotics, 36 (4), 182–191. 

Charlier, C. V. L., & Wicksell, S. D. (1924). On the dissection of frequency functions. Arkiv f. Matematik Astron. OchFysik. 

Chavosh, A., Halimi, A. B., Soheilirad, S., Ghajarzadehd,A., & Nourizadeh, A. (2011). Customer responsiveness and export performance of selected electronic equipment export companies in Malaysia. International Conference on Social Science and Humanity, 5(1), 124–127. 

Chen, L., & Intal, P. (2017). ASEAN and member states: transformation and integration. Retrieved from http://hdt.handle.net/11540/7430. 

Chetthamrongchai, P., Somjai, S., & Chankoson, T. (2020). The contribution of macroeconomic factors in determining the economic growth, export and the agricultural output in agri-based ASEAN economies. Entrepreneurship and Sustainability Issues, 7(3), 2043–2059. 

Chirieleison, C., & Scrucca, L. (2017). Event sustainability and transportation policy: A model-based cluster analysis for a cross-comparison of hallmark events. Tourism Management Perspectives, 24, 72–85. 

Chou, H. C., & Wang, D. (2007). Performanceof defaultrisk model with barrier option framework and maximumlikelihoodestimation:Evidencefrom Taiwan. Physic A:Statistical Mechanics and its Applications, 385(1), 270–280. 

Choudhary, D., & Robinson, A.L. (2014). A new approach to wireless channel modeling using finite mixture models. International Journal of Digital Information and Wireless Communications, 4, 169–183. 

Chowdhury, M. S. R., & Hossain, M.T. (2014). Determinants of exchange rate in Bangladesh: acasestudy. Journal of Economics and Sustainable Development, 5(1), 78–81. 

Clark, M. W. (1977). Gethen: a computer program for the decomposition of mixtures of two normal distributions by the method of moments. Computers and Geosciences, 3(2), 257–267. 

Cohen, A. C. (1967). Estimation in mixtures of two normal distributions. Technometrics, 9(1), 15–28. 

Cohen, A. C., & Helm, F. R. (1973). Estimation in the exponential distribution. Technometrics, 15(2), 415–418. 

Cole, S. R., Chu, H., & Greenland, S. (2014). Maximum likelihood, profile likelihood, and penalized likelihood:aprimer. American Journal of Epidemiology, 179(2), 252–260. 

Conceição, K. S., Andrade, M. G.,& Louzada, F. (2013). Zero-modified Poisson model: Bayesian approach, influence diagnostics, and an application to a Brazilian leptospirosis notification data. Biometrical Journal, 55(5), 661–678. 

Conway, P. (2012). The exchange rate as nominal anchor: a test for Ukraine. Journal of Comparative Economics, 40(3), 438–456. 

Cooper, G. F., & Herskovits, E. (1992). A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9(4), 309–347. 

Cox, D. R. (1959). The analysis of exponentially distributed life-times with two types of failure. Journal of the Royal Statistical Society, Series B, 21, 411–421. 

Culos, A. E., Andrews, J. L., & Afshari, H. (2020). An artificial bee colony algorithm for mixture model-based clustering. Communications in Statistics -Simulation and Computation. doi: 10.1080/03610918.2020.1779291 

Dain, J. A. (1994). A practical minimum distance method for syntax error handling. Computer Languages, 20(4), 239–252. 

Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incompletedata via EM algorithm. Journal of the Royal Statistical Society,B39, 1–38. 

Department of Finance. (2020). DOF to implement wage subsidy program for 3.4 million workers of small businesses. Retrieved from https://www.dof.gov.ph/dof-to-implement-wage-subsidy-program-for-3-4-m­workers-of-small-businesses/ 

Dettman, S. C., & Gomez, E. T. (2020). Political financing reform: politics, policies, and patronage in Malaysia. Journal of Contemporary Asia, 50(1), 36–55. 

Dilmaghani, A. K., & Tehranchian, A. M. (2015). The impact of monetary policies on the exchange rate: a GMM approach. Iranian Economic Review, 19(2), 177– 191. 

Dinov, I. D. (2008). Expectation maximization and mixture modelling tutorial. Retrieved from https://scholarship.org/content/qt1rb70972/qt1rb70972.pdf?t= krnebn 

Do, K. A., Muller, P., & Tang, F. (2005). A Bayesian mixture model for differential gene expression. Journal of the Royal Statistical Society: Series C (Applied Statistics), 54(3), 627–644. 

Doan, T. T. T. (2020). Working capital management and profitability of fisheries enterprises by applying GMM. International Transaction Journal of Engineering Management & Applied Sciences & Technologies, 11(5), 11A05E 

Duan, J. C., & Simonato, J. G. (2002). Maximum likelihood estimation of deposit insurance value with interest rate risk. Journal of Empirical Finance,9, 109– 132. 

Dunson, D. B. (2001). Commentary: practical advantages of Bayesian analysis of epidemiologic data. American Journal of Epidemiology, 153(12), 1222–1226. 

Eagle, R. F., Romanczyk, R. G., & Lenzenweger, M. F. (2010). Classification of children with autism spectrum disorders: A finite mixture modeling approach to heterogeneity. Research in Autism Spectrum Disorders, 4(4), 772–781. 

Eirola, E., & Lendasse, A. (2013). Gaussian mixture models for time series modelling, forecasting, and interpolation. International Symposium on Intelligent Data Analysis (pp. 162-173). Springer, Berlin, Heidelberg. 

Errighi, L., & Bodwell, C. (2017). Electrical and electronicmanufacturing in Thailand: exploring challenges and good practice in workplace. ILO Asia-Pacific Working Paper Series. 

Etz, A. (2018). Introduction to the Concept of Likelihood and Its Applications. Advances in Methods and Practices in Psychological Science, 1(1), 60–69. 

Fayomi, A., Mal, D., & Adham, S. (2019). Statistical inference of the exponentiated Kumaraswamy-Exponential distribution based on complete and type II censored samples. Advances And Applications in Statistics, 54(2), 273–288. 

Feng, X., & Xie, D. (2012). Bayesian Estimation of CIR Model. Journal of Data Science, 10, 271–280. 

Fisher, R. A. (1922). On the mathematical foundations of theoretical statistics. Philosophical Transactions of the Royal Society of London, 222, 309–368. 

Friedman, M. (1977), Nobel lecture: inflation and unemployment. Journal of Political Economics, 85(3), 451–472. 

Früwirth-Schnatter, S. (2006). Finite Mixture and Markov Switching Models. Springer Series in Statistics, Springer, New York. 

Fujii, Y., Kaneko, S., Nzou, S. M., Mwau, M., Njenga, S. M., Tanigawa, C., et al. (2014). Serological surveillance development for tropical infectious diseases using simultaneous microsphere-based multiplex assays and finite mixture models. PLoS Neglected Tropical Diseases, 8(7), e3040. 

Garrido, L., & Cuervo, E. C. (2013). Heteroscedastic Weibull-normal mixture models: aBayesian approach.Communications in Statistics -Theory and Methods, 43(2), 249–265. 

Geiger, L. T. (1991). Evaluating export expansion strategy for economicdevelopment: selected LDC’s. Eastern Economic Journal, 17(3), 319–330. 

Gholami, R., & Okhmatovski, V. (2020). Surface-Volume-Surface EFIE formulation for fast direct solution of scattering problem on general 3-d composite metal-dielectric objects. IEEE Transactions on Antennas and Propagation, 68(7), 5742–5747. 

Ghosh, D., & Chinnaiyan, A. M. (2008). Genomic outlier profile analysis: mixture models, nullhypotheses, and nonparametric estimation.Biostatistics, 10(1), 60– 69. 

Ghosh, S. K. (2009). Basics of Bayesian methods. Statistical Methods in Molecular Biology, 155–178. 

Ghosh, S. K., Mukhopadhyay, P., & Lu, J.C. (2006). Bayesian analysis ofzero-inflated regression models. Journal of Statistical Planning and Inference, 136(4), 1360– 1375. 

Gill, J. (2008). Bayesian Methods: a social and behavioral sciences approach, second edition. Chapman & Hall. 

Goh, S. K., & Lim, M. M. H. (2010). The impact of the global financial crisis: the case of Malaysia. Penang: Jutaprint. 

Hada, T., Avram, T. M., & Barbuta-Misu, N. (2018). The impact of EUR/RON exchangerate policy on Romanian exports. Economic and Applied Informatics. 

Hallegatte, S., Bangalore, M., Bonzanigo, L., Fay, M. Kane, T., Narloch, U., et al. (2016). Shock wave: managing the impacts of climate change on poverty. Washington: International Bank for Reconstruction and Development. 

Hamilton, J. D. (1989). A new approach to the economic analysis of non-stationary time series and the business cycle. Econometrica, 57, 357–384. 

Hamilton, J. D. (1994). Time series analysis. Princeton: Princeton University Press 

Han, A., Hong, Y., Wang, S., & Yun, X. (2016). A vector autoregressive moving average model for interval-valued time series data. Essays in Honor of Aman Ullah, 36, 417–460. 

Han, S., & Coulibaly, P. (2017). Bayesian flood forecasting methods: A review. Journal of Hydrology, 551, 340–351. 

Hardelid, P., Williams, D., Dezateux, C., Tookey, P., Peckham, C., Cubitt, W., et al. (2008). Analysis of rubella antibody distribution from new-born dried blood spots using finite mixture models. Epidemiology and Infection, 136(12), 1698– 1706. 

Hassan, A., Wani, S. A., Shafi, S., & Dar, S. A. (2022). Transmuted quasi akash distribution applicable to survival times data. Thailand Statistician, 20(2), 338– 356. 

Heo, W., Park, N., & Park, K. (2020). Classifying students using an expectation-perception survey about a hospitality laboratory class: Empirical research with the finite mixture model. Anatolia-International Journal of Tourism and Hospitality Research, 31(1), 50–61. 

Hernandez, J. A., & Phillips, I. W. (2006). Weibull mixture model to characterise end­to-end Internet delay at coarsetime-scales.IEE Proceedings -Communications, 153(2), 295–304. 

Hobbs, J. R., Moore, A. H., & James, W. (1984). Minimum-distanceestimation of the three parameters of the Gamma distribution, IEEE Trans. Reliability, 33 (3), 237–240. 

Hobbs, J. R., Moore, A. H., & Miller, R. M. (1985). Minimum-distance estimation of the parameters of the 3-parameter Weibull distribution, IEEE Trans. Reliability, 34, 495–496. 

Hong, M. C., Chu, E. Y., & Song, S. I. (2018). Exchange rate exposure and crude oil price: the case of an emerging market. Asian Academy of Management Journal of Accounting and Finance, 14(2), 157–184. 

Hu, M. K. (1962). Visual pattern recognition by moment invariants.IEEE Transactions on Information Theory, 8(2), 179–187. 

Hu, X., Johnson, V., Wong, W. H., & Chen, C. T. (1991).Bayesian image processing in magnetic resonance imaging. Magnetic Resonance Imaging, 9(4), 611–620. 

Hurvich, C. M.,& Tsai,C. (1990). Theimpact of model selection oninferenceinlinear regression. The American Statistician, 44(3), 214–217. 

Idris, Z. (2020). Positioning Malaysia in the realm of global uncertainty: analysing its concernand struggles of Pakatan Harapangovernment. Journal of International Studies, 16, 159–182. 

Imai, K.,& Tingley, D. (2011). A statistical method forempirical testing of competing theories. American Journal of Political Science, 56(1), 218–236. 

Imimole, B.,&Enoma, A. (2011).Exchangeratedepreciation and inflation in Nigeria.Business and Economics Journal. 

Institute for Economics and Peace. (2016). Global terrorism index 2016: measuring and understating the impact of terrorism. Retrieved from http://economicsand peace.org/wp-content/uploads/2016/11/Global-Terrorism-Index-2016.2.pdf 

Institute for Economics and Peace. (2018). Global terrorism index 2018: measuring and understating the impact of terrorism. Retrieved from http://visionof humanity.org/reports 

Inverardi, P. L. N., & Taufer, E. (2020). Outlier detection through mixtures with an improper component. Electronic Journal of Applied Statistical Analysis, 13(1), 146–163. 

Islam, R., Ghani, A. B. A., Mahyudin, E., & Manickam, N. (2017). Determinants of factorsaffecting inflation in Malaysia. International Journal of Economics and Financial Issues, 7(2), 355–364. 

Ismail, A. A., & Al-Harbi, M. M. (2020). On the Bayesian analysis of constant-stress life test model under type II censoring. Strength of Materials, 52(2), 307–316. 

Ismail, N. A., Talib, B. A., & Mokhtar, A. (2019). Export analysis of major commodities in Malaysia. In IOP Conference Series: Earth and Environmental Science, 327(1), 012002. 

Izzuddin, M. (2019). Malaysia in 2018 asea change in an election year. Asian Survey, 59(1), 147–155. 

Jakaitiene, A. (2018). Nonlinear Regression Models. Encyclopedia of Bioinformatics and Computational Biology, 1, 731–737 

Janssen, J., Selfe,J., Gichuru, P., Richards, J., Yosmaoglu, H. B., Sonmezer,E., Erande, R., Resteghini, P., & Dey, P. (2020). Hot and cold knees: exploring differences in patella skin temperature in patients with patellofemoral pain. Physiotherapy, 108, 55–62. 

Jaradat, M., Al-Zeaud H. A., & Al-Rawahneh, H. (2011). An econometric analysis of the determinants of inflation in Jordan. Journal of Middle Eastern Finance and Economics, 15, 121–132. 

Jentsch, C., Leucht, A., Meyer, M., & Beering, C. (2020). Empirical characteristic functions-based estimation and distance correlation for locally stationary processes. Journal of Time Series Analysis, 41(1), 110–133. 

Jha, M. K., Dey, S., & Tripathi, Y. M. (2019). Reliability estimation in a multicomponent stress strength based on unit-Gompertz distribution. International Journal of Quality and Reliability Management, 37(3), 428–450. 

John, C., Ekpenyong, E. J., & Nworn, C. C. (2019). Imputation of missing values in economicandfinancial time series data usingfiveprincipal component analysis approaches. CBN Journal of Applied Statistics, 10(1), 51–73. 

Kabir, S., Bloch,H., & Salim, R. A. (2018). Global financialcrisis andSoutheast Asian trade performance: Empirical evidence. Review of Urban & Regional Development Studies, 30(2), 114–144 

Kalyanam, K. (1996). Pricing decisions under demand uncertainty: A Bayesian mixture model approach. Marketing Science, 15(3), 207–221. 

Kamaruzzaman, Z. A., Isa, Z., & Ismail, M. T. (2012). Mixtures of normal distributions: application to bursa malaysia stock market indices. World Applied Sciences Journal, 16(6), 781–790. 

Kandil, M., & Mirzaie, I. A. (2002). Exchange rate fluctuations and disaggregated economic activity in the US: theory and evidence. Journal of International Money and Finance, 21(1), 1–31. 

Kappe, E., DeSarbo, W. S., & Medeiros, M. C. (2020). A smooth transition finite mixture model for accommodating unobserved heterogeneity. Journal of Business & Economic Statistics, 38(3), 580–592. 

Khalaj-Amirhosseini, M. (2007). Analysis of longitudinally inhomogeneous waveguides using the method of moments. Progress in Electromagnetics Research, 74, 57–67. 

Khan, M. S., & Senhadji, S. A. (2001). Threshold effects in the relationship between inflation and growth. IMF Staff Papers, 48(1), 1–21. 

Khodier, A. N. (2012). Towards inflation targeting in Egypt: the relationship between exchange rate and inflation. South African Journal of Economic and Management Sciences, 15(3), 325–332. 

Kiganda, E. O.,Obange, N., & Adhiambo, S. (2017). Therelationship between exports and inflation in Kenya: an aggregated econometric analysis. Asian Journal of Economics, Business and Accounting, 3(1), 1–12. 

Kim, S. Y., Huh, D., Zhou, Z., & Mun, E. Y. (2020). A comparison of Bayesian to maximum likelihood estimation for latent growth models in the presence of a binary outcome. International Journal of Behavioral Development, 44(5), 447– 457. 

King, E. N., &Ryan, T.P. (2002). A preliminary investigation of maximum likelihood logistic regression versus exact logistic regression. The American Statistician, 56(3), 163–170. 

Koch, H., & DeGiorgio, M. (2020). Maximum likelihood estimation of species trees from gene trees in the presence of ancestral population structure. Genome Biology and Evolution, 12(2), 3977–3995. 

Kong, Y. S., Abdullah, S., & Singh, S. S. K. (2022). Distribution characterisation of spring durability for road excitations using maximum likelihood estimation. Engineering Failure Analysis, 134, 106041. 

Krishna, H., & Malik, M. (2008). Reliability estimation in Maxwell distribution with Type-II censored data. International Journal of Quality & Reliability Management, 26(2), 184–195. 

Kuhner, M. K., & Felsenstein, J. (1994). A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates. Journal of Molecular Evolution, 11(3), 459–468. 

Kumar, S., & Chaturvedi, A. (2020). On a generalization of the positive exponential family of distributions and the estimation ofreliability characteristics.Statistica, 80(1), 57–77. 

Kuo, C. J., & Lu, S. L.(2005). Taiwan’s financial holding companies: an empirical investigation based on Markov regime-switching model. Applied Economics, 37(5), 593–605. 

Laplace, P. S. (1986). Memoir on the Probability of the Causes of Events. Statistical Science, 1(3), 364–378. 

Le, Q. H., Nguyen, B. N., & Tran, L. H. (2020). Policy credit and income inequality reduction in Vietnam: Anempiricalanalysis. International Journal of Advanced and Applied Sciences, 7(9), 68–74. 

Lee, S., & Na, O. (2005). Test for parameter change in stochastic processes based on conditional least-squares estimator. Journal of Multivariate Analysis, 93(2), 375–393. 

Lei, Y., Carlson, S., Yelland, L. N., Makrides, M., Gibson, R., & Gajewski, B. J. (2017). Comparison of dichotomized anddistributional approachesin rareevent clinical trial design:afixed Bayesian design. Journal of Applied Statistics,44(8), 1466– 1478. 

Li, C., &Hao, H. (2016). Likelihood and Bayesian estimation instress strength model from generalized exponential distribution containing outliers. International Journal of Applied Mathematics, 46(2), 155–159. 

Li, C., Zheng, J. J., Okamura, H., & Dohi, T. (2022). Parameter estimation of Markovian arrivals with utilization data. IEICE Transactions on Communications, E105B (1), 1–10. 

Li, L., Xu, Z., Xie, W., & Zhang, Z. (2020). A sensitivity analysis of bubble departure behavior in vertical channel nucleate boiling. International Journal of Thermal Sciences, 157, 106497. 

Lin, E. M. H., Sun, E. W., & Yu, M. T. (2020). Behavioural data-driven analysis with Bayesian method for risk management of financial services. International Journal of Production Economics, 107737. 

Liu, A., Song, H., & Blake, A. (2018). Modeling productivity shocks and economic growth using the Bayesian dynamic stochastic general equilibrium approach. International Journal of Contemporary Hospitality Management, 30(11), 3229–3249. 

Liu, F. X. (2017). Finite mixture model for the application in forestry. 2017 2nd International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2017), 1492–1497. 

Long, J. S. (1997). Regression models for categorical and limited dependent variables. United States of America: SAGEPublication. 

Long, J. S., & Freese, J. (2014). Regression models for categorical dependent variables using Stata. United States of America: Stata Corporation 

Lowe, R., Barcellos, C., Coelho, C. A. S.,Bailey, T. C., Coelho, G. E., Graham, G., et al.(2014).Dengueoutlook forthe World Cup in Brazil: an early warning model framework driven by real-time seasonal climateforecasts. The Lancet Infectious Diseases 14, 619–626. 

Lumjiak, S., Quang, N. T. T., Gan, C., & Treepongkaruna,S. (2018).Goodcoups, bad coups: evidence from Thailand’s financial markets. Investment Management and Financial Innovations, 15(2), 68–86. 

Maddala, G. S., & Kim, I. M. (1998). Unit Roots, Cointegration and Structural Change. UK: Cambridge University Press. 

Madigan, D., Ryan, P., Simpson, S., & Zorych, I. (2011). Bayesian methods in pharmacovigilance. Bayesian Statistics, 9, 421–438. 

Malaysia to be among top 20 largest exporting countries. (2016, August 16). The Star. Retrieved from https://www.thestar.com.my/business/business-news/2016/08/ 15/malaysia-to-be-among-top-20-largest-exporting-countries/ 

Malaysian Good and ServiceTax. (2014, Sept 4). Handbook for goods and services tax (GST) for business. Retrieved from http://gst.customs.gov.my/en/rg/SiteAssets/ general_guides/Handbook%20Vol1%2002092014%20Master.pdf 

Mamun, A. A., Rahman, M. K., Taufiq, M., & Muzzammir. (2015). A shift-share analysis of electrical and electronic products: an overview and assessment of export growth of Malaysia. Asian Social Science, 11(10), 330–338. 

Marino, M., Li D. P., Bavetta, S., & Cellini, M. (2020). The democratization process: An empirical appraisal of the role of political protest. European Journal of Political Economy, 63, 101881. 

Marroquin, J. L., Vemuri, B. C., Botello, S., Calderon, E., & Fernandez-Bouzas, A. (2002). An accurate and efficient Bayesian method for automatic segmentation of brain MRI. IEEE Transactions on Medical Imaging, 21(8), 934–945. 

Maurya, S. (2017). Factors affecting exchangerateand its impact on economy of India. Asian Journal of Research in Business Economic and Management, 7(8), 324­347. 

McCargo, D. (2017). Thailand in 2016: fade to cray. Asian Survey, 57(1), 150–156. 

McLachlan, G. J.,& Peel, D. (2001). Finite Mixture Models. New York: John Wiley & Sons. 

McLachlan, G. J. (2009). Model-Based Clustering. Comprehensive Chemometrics, 655–681. 

McLachlan, G., Peel, G., Basford, K., & Adams, P. (1999). The EMMIX software for the fitting of mixtures of normal and t-components. Journal of Statistical Software, 4(2). 

Menji, S. (2009). Determinants of recent inflation in Ethiopia. Unity University. Retrieved from https://mpra.ub.uni-muenchen.de/29668/1/Determinants_of_ Recent_ Inflation_in_Ethiopia.pdf 

Ministry of Finance Malaysia. (2021). Economic outlook 2021. Kuala Lumpur: Percetakan Nasional Malaysia Berhad. 

Ministry of International Trade and Industry. (2015). Electrical & Electronics   Industry. Retrieved from http://www.miti.gov.my/index.php/pages/view/2482. 

Ministry of International Trade and Industry. (2018). National policy on industry 4.0. Kuala Lumpur:MITI. Retrieved from https://www.miti.gov.my/miti/resources/ National%20Policy%20on%20Industry%204.0/Industry4WRD_Final.pdf 

Miura, K. (2011). An introduction to maximum likelihood estimation and information geometry. Interdisciplinary Information Sciences, 17(3), 155–174. 

Monfared, S. S., & Akin, F. (2017). The relationship between exchange rate and inflation rate: the case of Iran. European Journal of Sustainable Development, 6(4), 329–340. 

Mortazavi, R., & Lundberg, M. (2020). Expenditure-based segmentation of tourists taking into account unobserved heterogeneity: The case of Venice. Tourism Economics, 26(3), 475–499. 

Mufudza, C., & Erol, H. (2016). Poisson mixture regression models for heart disease prediction. Computational and Mathematical Methods in Medicine, 1-10. 

Muhammad, N. M. N., & Yaacob, H. C. (2008). Export competitiveness of Malaysian electronicand electrical (E&E)product:comparativestudyof China, Indonesia and Thailand. International Journal of Business and Management, 3(7), 65–75. 

Musila, J. W. (2002). An econometric model of the Malawian economy. Economic Modelling, 19(2), 295–330. 

Nasir, S., & Al-Anber, N. J. (2012). A comparison of the Bayesian and other methods for estimation of reliability function for burr-XII distribution. Journal of Mathematics and Statistics, 8(1), 42–48. 

National Economic & Development Authority. (2015). Rapid rise in food prices, typhoon Yolanda drive up poverty incidence among Filipinos in first half of 2014. Retrieved from https://www.neda.gov.ph/rapid-rise-food-prices­typhoon-yolanda-drive-pove rty-incidence-among-filipinos-first-half-2014per­capita-incomes-increased-food-inflation-negated-benefits-poor-neda/ 

Ndoye, A. A., & Lubrano, M. (2014). Tournaments and superstar models:amixtureof two pareto distributions. Economic Well-Being and Inequality: Papers from the Fifth ECINEQ Meeting, 449–479. 

Newcomb, S. (1886). A generalized theory of the combination of observations so as to obtain the best result. American Journal of Mathematics, 8, 343–366. 

Ng, S. K., Krishnan. T., & McLachlan, G.J. (2004). The EM algorithm. In Gentle, J., Hardle, W. and Mori, Y. (eds), Handbook of Computational Statistics Vol. 1. Springer-Verlag, New York. 137–168. 

Noorazlina, A., Sakinah, M. Z., & Fadli Fizari, A. B. A. (2011). Fixed versus flexible exchange rate systems. International Accounting and Business Conferences 2011. 

Nord, C. L., Valton, V., Wood, J., & Roiser, J. P. (2017). Power-up: a reanalysis of ‘power failure’ in neuroscience using mixture modeling. The Journal of Neuroscience, 37(34), 8051–8061. 

Ouedraogo, R., Sawadogo, R., & Sawadogo, H. (2020). Private and public investment in sub-Saharan Africa: the role of instability risks. Economic Systems, 44(2), 100787. 

Ozturk, E.(2018).Theimpact of R&D sourcing strategies on basic and developmental R&D in emerging economies. European Journal of Innovation Management, 21(4), 522–542. 

Pacella, M., & Papadia, G. (2022). Finite mixturemodels forclustering auto-correlated sales series data influenced by promotions. Computation, 10 (2), 23. 

Pandey, B. N., Dwivedi, N., & Bandyopadhyay, P. (2011). Comparison between Bayesian and maximum likelihood estimation of scale parameter in Weibull distribution with known shape under Linex loss function. Journal of Scientific Research, 55, 163–172. 

Parr, W. C., & Schucany, W.R. (1980). Minimum distance and robust estimation. Journal of the American Statistical Association, 75(371), 616–624. 

Parveen, S., Khan, A. Q., & Ismail, M. (2012). Analysis of the factors affecting exchange rate variability in Pakistan. Academic Research International, 2(3), 670–674. 

Patel, C. I.,& Patel, R. (2011). Gaussian mixturemodel based moving object detection from video sequence.Proceedings of the International Conference & Workshop on Emerging Trends in Technology -ICWET ’11, 698–702. 

Pearson, K. (1894). Contributions to the theory of mathematics evolution. Philosophical Transactions of the Royal Society of London, A185, 71–110. 

Peterson, A. (2005). Identifying the Determinants of Exchange Rate Movements (Master Thesis). Jonkoping international Business School, Jonkoping University. 

Phillips, P. C. B., & Yu, J. (2009). Maximum likelihood and gaussian estimation of continuous time models in finance. Handbook of Financial Time Series, 497– 530. 

Phoong, S. W., Ismail M. T., & Sek, S. K. (2014). A comparison between MS-VECM and MS-VECMX on economic time series data. AIP Conference Proceedings, 1605, 810. doi: 10.1063/1.4887694 

Phoong, S. Y.,& Ismail, M. T. (2013). Rubber priceeffect on exchangerate:aBayesian mixture model approach. Information Management and Business Review, 5(6), 263–269. 

Phoong, S. Y., & Ismail, M. T. (2014). A study of finite mixture model: Bayesian approachon financial timeseriesdata. In: AIP Conference Proceedings, March 2014, Penang 

Phoong, S. Y., & Ismail, M. T. (2014). Finite mixture model: a maximum likelihood estimation approach on time series data. In AIP Conference Proceedings, September, Sarawak. 

Pravitasari, A. A., Iriawan, N., Fithriasari, K., Purnami, S. W., Irhamah, & Ferriastuti,W. (2020). A Bayesian neo-normal mixture model (nenomimo) for MRI-based brain tumor segmentation. Applied Sciences-Basel, 10(14), 4892. 

Psutka, J. V., & Psutka, J. (2015, September). Sample size for maximum likelihood estimates of Gaussian model. In International Conference on Computer Analysis of Images and Patterns (pp. 462–469). Springer, Cham. 

Purba, S. A., Surtarman.,& Darnius, O. (2017). Maximum likelihoodbased on Newton Raphson, fishering scoring and expectation maximization algorithm application on accident data. International Journal of Advanced Research, 6(1), 965–969. 

Qamruzzaman, M., Karim, S., & Wei, J. (2019). Does asymmetric relation exist between exchange rate and foreign direct investment in Bangladesh? Evidence from nonlinear ARDL analysis. Journal of Asian Finance, Economics and Business, 6(4), 115–128. 

Quandt, R. E. (1958). The estimation of the parameters of a linear regression system obeying two separate regimes. Journal of the American Statistical Association, 53(284), 873–880. 

Rahim, M., Suriadi, L. O., & Milia, H. (2016). Analysis of exports of marine fishery commodities in southeast Sulawesi. International Journal of Humanities and Social Science, 6(10), 53–62. 

Raj, B. (2002). Asymmetry of Business Cycles: The Markov-Switching Approach. In: Ullah, A., Wan, A. T. K. & Chaturvedi, A. (eds.). Handbook of Applied Econometrics and Statistical Inference. Marcel Dekker Inc, United States. 

Rasiah, R., Cheong, K. C., & Doner, R. (2014). Southeast Asiaand the Asian and global financial crises. Journal of Contemporary Asia, 44(4), 572–580. 

Rasiah, R., Yap, X. S., & Chandran Govindaraju, V. G. R. (2014). Crisis effects on the electronics industry in Southeast Asia. Journal of Contemporary Asia, 44(4), 645–663. 

Ratner, M., & Nerurkar, N. (2011). Middle East and North Africa unrest: implications for oil and natural gas markets. DIANE Publishing. 

Roberts, S. J., Husmeier, D., Rezek, I., & Penny, W. (1998). Bayesian approaches to Gaussian mixture modeling. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(11), 1133–1142. 

Rodrigues, J. (2003). Bayesian analysis of zero-inflated distributions. Communications in Statistics -Theory and Methods, 32(2), 281–289. 

Rozelle, S. D., & Sumner, D. A. (2003). Agricultural Trade and Policy in China: Issues, Analysis and Implications. London: Ashgate Publishing. 

Ruhi, S., Sarker, S., & Karim, M. R. (2015). Mixture models for analyzing product reliability data: a case study. SpringerPlus 4,634 

Saggu, A., & Anukoonwattaka, W. (2015). Commodity price crash: risks to exports and economic growth in Asia-Pacific LDCs and LLDCs. (Trade Insights: Issue No. 6). 

Šaliga, J., Kollár, I., Michaeli, L., Buša, J., Lipták, J., & Virosztek, T. (2013). A comparison of least squares and maximumlikelihood methods usingsine fitting in ADC testing. Measurement, 46(10), 4362–4368. 

Samphantharak, K. (2014). Natural disasters and the economy: some recent experiences from Southeast Asia. Asian-Pacific Economic Literature, 28(2), 33–51. 

Sandique-Carlos, R. (2012, May 4). Philippine inflation gathers pace in April. Wall Street Journal (Online) Retrieved from https://www.wsj.com/articles/ SB1000142405270230474370457738308109 7031786 

Satishkumar, L. V., & Vandana, B. (2017). Human skin detection using histogram processing and Gaussian Mixture Model based on colour spaces. 2017 International Conference on Intelligent Sustainable Systems (ICISS), Palladam, India 

Schwartz, R. S., & Mueller, R. L. (2010). Branch length estimation and divergence dating: estimates of error in Bayesian and maximum likelihood frameworks. BMC Evolutionary Biology, 10(5). 

Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. 

Senate of the Philippines. (2011, October). Economic report. Retrieved from http://legacy.senate.gov.ph/publications/ER%202011-01%20-%20October%2 02011.pdf 

Shah, A. U. M., Safri, S. N. A., Thevadas, R., Noordin, N. K., Rahman, A. A., Sekawi, Z., et al. (2020). COVID-19 outbreak in Malaysia: actions taken by the Malaysian government. International Journal of Infectious Diseases, 97, 108– 116. 

Shi, F. R., Li, H. L., Yang, S. X., Tuo, X. G., & Lin, M. S. (2020). Novel maximum likelihoodestimation of clockskew in one-way broadcast timesynchronization. IEEE Transactions on Industrial Electronics, 67(11), 9948–9957. 

Singh, C. H., & Ladusingh, L. (2009). Inpatient length of stay: afinite mixturemodeling analysis. The European Journal of Health Economics, 11(2), 119–126. 

Smets, F., & Wouters, R. (2003). Anestimated dynamic stochastic general equilibrium model of the Euro area. Journal of the European Economic Association, 1(5), 1123–1175. 

Smith, F. W., & Wright, M. H. (1971). Automatic ship photo interpretation by the method of moments. IEEE Transactions on Computers, C-20(9), 1089–1095. 

Smith, R. L., & Naylor, J. C. (1987). A comparison of maximum likelihood and Bayesian estimators forthethree-parameter Weibulldistribution. Journal of the Royal Statistical Society. Series C (Applied Statistics), 36(3), 358–369. 

Smoll, N. R., Mathews, J. D., & Scurrah, K. J. (2020). CT scans in childhood predict subsequent brain cancer: Finite mixture modelling can help separate reverse causation scans from those that may be causal. Cancer Epidemiology, 67, 101732. 

Son, Y. S., & Oh, M. (2006). Bayesian estimation of the two-parameter gamma distribution.Communications in Statistics -Simulation and Computation, 35(2), 285–293. 

Stacey, A. G. (2020). Robust parameterisation of ages of references in published research. Journal of Informetrics, 14(3), 101048. 

Stacey, A. G. (2021). Ages of cited references and growth of scientific knowledge: an explication of the gammadistributionin business and management disciplines. Scientometrics, 126(1), 619–640. 

Stepchenko, A., Chizhov, J., Aleksejeva, L., & Tolujew, J. (2016). Nonlinear, non-stationary and seasonal time series forecasting usingdifferent methods coupled with data processing. Procedia Computer Science, 104, 578–585. 

Stewart, I. J., Hicks, A. C., Taylor, I. G., Thorson, J. T., Wetzel, C., & Kupshus, S. (2013). A comparison of stock assessment uncertainty estimates using maximum likelihood and Bayesian methods implemented with the same model framework. Fisheries Research, 142, 37–46. 

Suesse, B., Lago, L., Westley-Wise, V., Masso, M., Cuenca J., & Pai, N. (2021). Application of mixture distributions foridentifying thresholds of frequent and high inpatient mental health service use in longitudinal data. Journal of Mental Health. 

Sulaiman, N. F. C., Sanusi, N. A., & Muhamad,S. (2020). Surveydataset of Malaysian perception on rising cost of living. Data in Brief, 28, 104910. 

Tamandi, M., & Jamalizadeh, A. (2020). Finite mixturemodelingusingshapemixtures of the skewscalemixtures of normal distributions.Communications in Statistics -Simulation and Computation, 49(12), 3345–3366. 

Teh, C. H., & Chin, R. T.(1988). On imageanalysis by the methods of moments. IEEE Transactions on Pattern Analysis and Machine Intelligence, 10(4), 496–513. 

Transparency International. (2019). Corruption Perception Index 2019.Retrieved from https://www.transparency.org/files/content/pages/2019_CPI_Report_EN.pdf 

Tuck, C. T., & Wong, K. N. (2008). The effects of exchange rate variability on Malaysia’s disaggregated electrical exports. Journal of Economics Studies, 35(2), 154–169. 

Tuke, J., Nguyen, A., Nasim, M., Mellor, D., Wickramasinghe, A., Bean, N., & Mitchell, L. (2019). Pachinko Prediction: a Bayesian method for event prediction from social media data. Information Processing & Management, 102147. 

Uddin, H., & Khanam, M. J. (2017). Import, export and economic growth: the case of lower income country. Journal of Business and Management, 19(1), 37–42. 

Umezaki, S. (2019). The Malaysian economy after the global financial crisis: international capital flows, exchange rates and policy responses. Public Policy Review, Policy Research Institute, Ministry of Finance Japan, 15(1), 69–98. 

United Nations International Children's Emergency Fund. (2020, July). Social impact assessment of Covid-19 in Thailand. Retrieved from https://www.unicef.org/thailand/media/5071/file/Social%20Impact%20Assess ment%20of%20COVID19%20in%20Thailand.pdf 

Valsamis, E. M., Husband, H., & Chan, G. K. W. (2019). Segmented linear regression modelling of time series of binary variables in healthcare. Computational and Mathematical Methods in Medicine, 1-7. 

Van Wieringen, W. N., & Van DeWiel, M. A. (2008). Nonparametrictesting forDNA copy number induced differential mRNA gene expression. Biometrics, 65(1), 19–29. 

Venkadasalam S. (2015). The determinant of consumer price index in Malaysia. Journal of Economics, Business and Management. 3(12), 1115–1119. 

Vicuna, M. I., Palma, W., & Olea, R. (2019). Minimum distance estimation of locally stationary moving averageprocesses. Computational Statistics & Data Analysis, 140, 1–20. 

Vijayasri, G. V. (2013). The importance of international trade in the world.International Journal of Marketing, Financial Service and Management Research, 2(9), 111–119. 

Vo, D. H., Vo, A. T., & Zhang, Z. Y. (2019).Exchangerate volatility and disaggregated manufacturing exports: evidencefrom an emerging country.Journal of Risk and Financial Management, 12(1). 

Walters, C., & Ludwig, D. (1994). Calculation of Bayes posterior probability distributions forkey population parameters. Canadian Journal of Fisheries and Aquatic Sciences, 51(3), 713–722. 

Wang, D. Q., Fan, Q. H., & Ma, Y. (2020). An interactive maximum likelihood estimation method for multivariable Hammerstein systems. Journal of the Franklin Institute-Engineering and Applied Mathematics, 357(17), 12986– 13005. 

Wang, D., Kaplan, L., & Abdelzaher, T. F. (2014). Maximum likelihood analysis of conflicting observations in social sensing. ACM Transactions on Sensor Networks, 10(2), 1–27. 

Wang, X., & Peng, Z. (2014). Method of moments for estimating uncertainty distributions. Journal of Uncertainty Analysis and Application, 2(5). 

Wang, Y. D., & Tang, Y. C. (2019). Statistical analysis of accelerated temperature cycling test based on Coffin-Manson model. Communications in Statistics ­Theory and Methods, 49(15), 3663–3680. 

Wang, Z., Wang, L., Tan, Y., & Yuan, J. (2021). Fault detection based on Bayesian network and missing data imputation for building energy systems. Applied Thermal Engineering, 182, 116051. 

Wardhono, A., Nasir, M. A., Qori’ah, C. G., & Indrawati, Y. (2021). Movement of inflation and new keynesian Phillips curve in ASEAN. Economies, 9(1), 34. 

Welsh, B. (2018). “Saviour” politics and Malaysia’s 2018 electoral democratic breakthrough: rethinking explanatory narratives and implications. Journal of Current Southeast Asian Affairs, 37(3), 85–108. 

Wiens, D. P., Cheng, J., & Beaulieu, N. C. (2003). A class of method of moments estimators forthetwo-parametergammafamily. Park. J. Statist. 29(1),129–141. 

Wolfe, J. H. (1967). NORMIX: Computational methods for estimating the parameters of multivariate normal mixture distributions.Technical bulletin USNPRA SRM 68-2. 

Wolfowitz, J. (1957). The minimum distance method. Annals of Mathematical Statistics, 28(1), 75–88 

Woodward, W. A., Parr, W. C., Schucany, W. R., & Lindsey, H. (1984). A comparison of minimum distance and maximum likelihood estimation of a mixture proportion. Journal of the American Statistical Association, 79(387), 590–598. 

World Bank. (2020). Thailand economic monitor: Thailand in the time of Covid-19. Washington: International Bank forReconstruction and Development. 

Wu, D. B. C., Tsai,Y. W., & Wen, Y. W. (2012). Bayesian cost-efficientness analysis for censored data: an application to antiplatelet therapy. Journal of Medical Economics, 15(3), 434–443. 

Wu, N., Song, X. (Ben), Yao, R., Yu, Q., Tang, C., & Zhao, S. (2020). A Bayesian sample selection model based on normal mixture to investigate household car ownership and usage behavior. Travel Behaviour and Society, 20, 36–50. 

Wu, Y. H., & Yang, P.K. (2020). Optimal estimation of gaussian mixtures via denoised method of moments. Annals of Statistics, 48(4), 1981–2007. 

Xu, J. Y., Mao, Q. L., & Tong, J. D. (2016). The impact of exchange rate movements on multi-product firms’ export performance: Evidence from China. China Economic Review, 39, 46–62. 

Xu, J., & Ma, J. (2017). Fitting finite mixture models using iterative Monte Carlo classification. Communications in Statistics -Theory and Methods, 46(13), 6684–6693. 

Yaghoubi, S., & Farnoosh, R. (2020). Model-Based Filtering via Finite Skew Normal Mixture for Stock Data. Journal of Statistical Theory and Applications, 19(3), 391–396. 

Yeung, K. Y., Bumgarner, R. E., & Raftery, A. E. (2005). Bayesian model averaging: development of an improved multi-class, gene selection and classification tool for microarray data. Bioinformatics, 21(10), 2394–2402. 

Ying, R., Yin, F. M.,Jiang, L., Li, Z.F., Huang, J. R., Wang, Y. Y.,et al. (2019).Fitting methods and seasonality effects on the assessment of pelagic fish communities in Daya Bay, China. Ecological Indicators, 103, 346–354. 

Yolanda, Y. (2017). Analysis of factors affecting inflation and its impact on human development index and poverty in Indonesia. European Research Studies Journal, 20(4), 38–56. 

Yonus, M., & Hassan, S. A. (2019). Probabilistic flood analysis of Indus river flow. Punjab University Journal of Mathematics, 51(8), 129–140. 

Yu, K. D. S., Aviso, K. B., Santos, J. R., & Tan, R. R. (2020). Theeconomicimpact of lockdowns: a persistent inoperability input-output approach. Economies, Multidisciplinary Digital Publishing Institute, 8(4), 109. 

Yu, L., Chen, D. G., & Liu, J. (2021). Efficient and direct estimation of the variance– covariance matrix in EM algorithm with interpolation method. Journal of Statistical Planning and Inference, 211, 119–130. 

Yukutake, N., & Moriizumi, Y. (2020). Credit constraints and the delay of homeownership by young households in Japan. International Journal of Housing Markets and Analysis, 13(1), 56–76. 

Zhang, F. P., Yang, J. J., & Ye, M. (2020). A nonparametric maximum likelihood estimation for biased-sampling data with zero-inflated truncation. Economics Letters, 194, 109399 

Zhang, H., & Huang, Y. (2015). Finite mixturemodels and theirapplications:areview. Austin Biometrics and Biostatistics, 2(1), 1–6. 

Zhang, S., Tao, M., Niu, X. F., & Huffer, F. (2020). Time-varying gaussian-cauchy mixture models for financial risk management. Florida State University. Retrieved from https://arxiv.org/pdf/2002.06102.pdf 

Zhang, T.,& Xie, M. (2007). Failure data analysis with extended Weibull distribution. Communications in Statistics -Simulation and Computation, 36(3), 579–592. 

Zhao, J. F., & Sullivan, C. J. (2019). Detection andparameter estimation of radioactive sources with mobile sensor networks. Radiation Physics and Chemistry, 155, 265–270.