404
Views
3
CrossRef citations to date
0
Altmetric
Articles

Modified maximum likelihood estimator under the Jones and Faddy's skew t-error distribution for censored regression model

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 2136-2151 | Received 13 Sep 2018, Accepted 18 Jun 2020, Published online: 30 Jun 2020

References

  • S. Acitas, P. Kasap, B. Senoglu, and O. Arslan, One-step M-estimators: Jones and Faddy's skewed t distribution, J. Appl. Stat. 40 (2013), pp. 1545–1560. doi: 10.1080/02664763.2013.788620
  • S. Acitas, B. Senoglu, Y.M. Kantar, and I. Yenilmez, Estimation for the censored regression model with the Jones and Faddy's skew t distribution: Maximum likelihood and modified maximum likelihood estimation methods, International Statistics Congress (ISC17), Ankara, Turkey, 6-8 Dec 2017, p. 53.
  • F.G. Akgul and B. Senoglu, Inference for the Jones and Faddy's skewed t-distribution based on progressively type-II censored samples, Gazi University J. Sci. 30 (2017), pp. 1–17.
  • T. Amemiya, Regression analysis when the dependent variable is truncated normal, Econometrica 41 (1973), pp. 997–1016. doi: 10.2307/1914031
  • T. Amemiya, Tobit models: A survey, J. Econom. 24 (1984), pp. 3–61. doi: 10.1016/0304-4076(84)90074-5
  • A. Arabmazar and P. Schmidt, An investigation of the robustness of the Tobit estimator to non-normality, Econometrica 50 (1982), pp. 1055–1063. doi: 10.2307/1912776
  • R.B. Arellano-Valle, L.M. Castro, G. Gonzalez-Farias, and K.A. Munoz-Gajard, Student-t censored regression model: Properties and inference, Stat. Methods Appl. 21 (2012), pp. 453–473. doi: 10.1007/s10260-012-0199-y
  • M.T. Arslan and B. Senoglu, Type II censored samples in experimental design under Jones and Faddy's skew t distribution, Iranian J. Sci. Technol. Trans A: Sci. 42 (2018), pp. 2145–2157. doi: 10.1007/s40995-017-0398-3
  • K.O. Bowman and L.R. Shenton, Asymptotic skewness and the distribution of maximum likelihood estimators, Commun. Stat. Theory Method 27 (1998), pp. 2743–2760. doi: 10.1080/03610929808832252
  • S.B. Caudill, A partially adaptive estimator for the censored regression model based on a mixture of normal distributions, Stat. Methods Appl. 21 (2012), pp. 121–137. doi: 10.1007/s10260-011-0182-z
  • S.R. Cosslett, Efficient semiparametric estimation of censored and truncated regressions via a smoothed self-consistency equation, Econometrica 72 (2004), pp. 1277–1293. doi: 10.1111/j.1468-0262.2004.00532.x
  • M.F. Desousa, H. Saulo, V. Leiva, and P. Scalco, On a tobit Birnbaum Saunders model with an application to medical data, J. Appl. Stat. 45 (2018), pp. 932–955. doi: 10.1080/02664763.2017.1322559
  • W.H. Greene, Econometric Analysis, 7th ed., Pearson Education, Upper Saddle River, NJ, 2012.
  • D. Gujarati, Econometrics by Example, Palgrave Macmillan, London, UK, 2014.
  • C. Gustafson, T. Abbas, D. Bolin, and F. Tufvesson, Tobit maximum-likelihood estimation of censored pathloss data, Technical report, Dept. of Electrical and Information Technology, Lund University, Sweden, 2015.
  • J. Heckman, The common structure of statistical models of truncation, sample selection and limited dependent variables and a sample estimator for such models, Ann. Econ. Soc. Meas. 5 (1976), pp. 475–492.
  • M.Q. Islam and M.L. Tiku, Multiple linear regression model under nonnormality, Commun. Stat. Theory Methods 33 (2004), pp. 2443–2467. doi: 10.1081/STA-200031519
  • M.C. Jones and M.J. Faddy, A skew extension of the t-distribution, with applications, J. R. Stat. Soc: Ser. B (Stat. Methodol.) 65 (2003), pp. 159–174. doi: 10.1111/1467-9868.00378
  • Y.M. Kantar and B. Senoglu, A comparative study for the location and scale parameters of the Weibull distribution with given shape parameter, Comput. Geosci. 34 (2008), pp. 1900–1909. doi: 10.1016/j.cageo.2008.04.004
  • Y.M. Kantar, I. Usta, and S. Acitas, A Monte Carlo simulation study on partially adaptive estimators of linear regression models, J. Appl. Stat. 38 (2011), pp. 1681–1699. doi: 10.1080/02664763.2010.516389
  • M. Karlsson and T. Laitila, Finite mixture modeling of censored regression models, Stat. Papers 55 (2014), pp. 627–642. doi: 10.1007/s00362-013-0509-y
  • S. Khan and J.L. Powell, Two-step estimation of semiparametric censored regression models, J. Econ. 103 (2001), pp. 73–110. doi: 10.1016/S0304-4076(01)00040-9
  • R.A. Lewis and J.B. McDonald, Partially adaptive estimation of the censored regression model, Econ. Rev. 33 (2014), pp. 732–750. doi: 10.1080/07474938.2012.690691
  • G. Martinez-Florez, H. Bolfarine, and H.W. Gomez, The alpha-power Tobit model, Commun. Stat. Theory Methods 42 (2013), pp. 633–643. doi: 10.1080/03610926.2011.630770
  • J.B. McDonald and S.B. White, A comparison of some robust, adaptive, and partially adaptive estimators of regression models, Econom. Rev. 12 (1993), pp. 103–124. doi: 10.1080/07474939308800255
  • J.B. McDonald and Y.J. Xu, A comparison of semi-parametric and partially adaptive estimators of the censored regression model with possibly skewed and leptokurtic error distributions, Econ. Lett. 51 (1996), pp. 153–159. doi: 10.1016/0165-1765(96)00816-6
  • C.G. Moon, A Monte Carlo comparison of semiparametric Tobit estimators, J. Appl. Econ. 4 (1989), pp. 361–382. doi: 10.1002/jae.3950040405
  • T. Mroz, The sensitivity of an empiricial model of married women's hours of work to economic and statistical assumptions, Econometrica 55 (1987), pp. 765–799. doi: 10.2307/1911029
  • A. Pagan and A. Ullah, Nonparametric Econometrics, Cambridge University Press, Cambridge, 1999.
  • J.L. Powell, Least absolute deviations estimation for the censored regression model, J. Econ. 25 (1984), pp. 303–325. doi: 10.1016/0304-4076(84)90004-6
  • J.L. Powell, Symetrically trimmed least squares estimation for Tobit models, Econometrica 54 (1986), pp. 1435–1460. doi: 10.2307/1914308
  • S. Punthenpura and N.K. Sinha, Modified maximum likelihood method for robust estimation of system parameters from very noisy data, Automatica 22 (1986), pp. 231–235. doi: 10.1016/0005-1098(86)90085-3
  • B. Senoglu and M.L. Tiku, Censored and truncated samples in experimental design under non-normality, Stat. Methods 6 (2004), pp. 173–199.
  • M.L. Tiku, Estimating the mean and standard deviation from a censored normal sample, Biometrika 54 (1967), pp. 155–165. doi: 10.1093/biomet/54.1-2.155
  • M.L. Tiku, Estimating the parameters of normal and logistic distributions from censored samples, Aust. J. Stat. 10 (1968), pp. 64–74. doi: 10.1111/j.1467-842X.1968.tb00216.x
  • M.L. Tiku and R.P. Suresh, A new method of estimation for location and scale parameters, J. Stat. Plan. Inference 30 (1992), pp. 281–292. doi: 10.1016/0378-3758(92)90088-A
  • J. Tobin, Estimation of relationships for limited dependent variables, Econometrica 26 (1958), pp. 24–36. doi: 10.2307/1907382
  • I. Usta and Y.M. Kantar, On the performance of the flexible maximum entropy distributions within partially adaptive estimation, Comput. Stat. Data Anal. 55 (2011), pp. 2172–2182. doi: 10.1016/j.csda.2011.01.010
  • D.C. Vaughan, On the Tiku-Suresh method of estimation, Commun. Stat. Theory Methods 21 (1992), pp. 329–340. doi: 10.1080/03610929208830788
  • D.C. Vaughan, Generalized secant hyperbolic distribution and its properties, Commun. Stat. Theory Methods 32 (2002), pp. 219–238. doi: 10.1081/STA-120002647
  • D. Vncent, BCTOBIT: Stata module to produce a test of the tobit specification, Statistical Software Components S457163, Boston College Department of Economics, 2010.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.