BAYESIAN ANALYSIS OF TOBIT QUANTILE REGRESSION WITH ADAPTIVE LASSO PENALTY IN HOUSEHOLD EXPENDITURE FOR CIGARETTE CONSUMPTION
(1) Department of Mathematics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University, Indonesia
(2) Department of Mathematics, Faculty of Mathematics and Natural Sciences, Gadjah Mada University, Indonesia
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J. Tobin, “Estimation of Relationships for Limited Dependent Variables,” Econometrica, vol. 26, no. 1, pp. 24–36, 1985, [Online]. Available: https://www-jstor-org.ezproxy.ugm.ac.id/stable/1907382?seq=1.
J. L. Powell, “Censored regression quantiles,” J. Econom., vol. 32, no. 1, pp. 143–155, 1986, doi: https://doi.org/10.1016/0304-4076(86)90016-3.
R. Tibshirani, “Regression Shrinkage and Selection Via the Lasso,” J. R. Stat. Soc. Ser. B, vol. 58, no. 1, pp. 267–288, 1996, doi: 10.1111/j.2517-6161.1996.tb02080.x.
H. Zou, “The Adaptive Lasso and Its Oracle Properties,” J. Am. Stat. Assoc., vol. 101, no. 476, pp. 1418–1429, 2006, doi: 10.1198/016214506000000735.
Cintiani, “Pemodelan Regresi Kuantil (Studi Kasus Pengeluaran Rumah Tangga untuk Konsumsi Rokok),” Program Magister Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, 2017.
R. Koenker, Quantile Regression. Cambridge: Cambridge University Press, 2005.
R. Alhamzawi and K. Yu, “Conjugate Priors and Variable Selection for Bayesian Quantile Regression,” Comput. Stat. Data Anal., vol. 64, pp. 209–219, 2012, doi: https://doi.org/10.1016/j.csda.2012.01.014.
W. H. Greene, Econometric Analysis Internastional Edition. UK: Pearson Education, 2012.
G. James, D. Witten, T. Hastie, and R. Tibshirani, An Introduction to Statistical Learning - with Applications in R. New York: Springer, 2013.
F. Mosteller and J. Tukey, Data Analysis and Regression: A Second Course in Statistics. Boston, USA: Addison-Wesley, 1977.
R. Koenker and G. Bassett, “Regression Quantiles,” Econometrica, vol. 46, no. 1, p. 33, 1978, doi: 10.2307/1913643.
R. Alhamzawi, “Tobit Quantile Regression with the adaptive Lasso penalty,” no. 1681 6870, pp. 1–19, 2013, [Online]. Available: https://www.researchgate.net/publication/258834905_Tobit_Quantile_Regression_with_the_adaptive_Lasso_penalty.
H. Kozumi and G. Kobayashi, “Sampling Methods for Bayesian Quantile Regression,” J. Stat. Comput. Simul., vol. 81, no. 11, pp. 1565–1578, 2011, doi: https://doi.org/10.1080/00949655.2010.496117.
D. F. Andrews and C. L. Mallows, “Scale Mixtures of Normal Distributions Author,” Society, vol. 36, no. 1, pp. 99–102, 2010.
D. van Ravenzwaaij, P. Cassey, and S. D. Brown, “A simple introduction to Markov Chain Monte–Carlo sampling,” Psychon. Bull. Rev., vol. 25, no. 1, pp. 143–154, 2018, doi: 10.3758/s13423-016-1015-8.
B. Walsh, “Markov Chain Monte Carlo and Gibbs Sampling,” Lect. Notes EEB 581, vol. 581, no. April, p. 24, 2004, [Online]. Available: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.4064.
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DOI: https://doi.org/10.26714/jsunimus.10.2.2022.25-33
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