t-distribution modeling using the available statistical software

Computational Statistics and Data Analysis

Volumn 25, Issue 2, 1997, Pages 181-206

  Jamshidian, Mortaza ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

BMDP LE; Linear regression; Nonlinear regression; Normal independent distribution; Robust estimation; SAS NLIN

Indexed keywords

ALGORITHMS; COMPUTER SOFTWARE; ERROR STATISTICS; ESTIMATION; FUNCTIONS; STATISTICAL METHODS;

LINEAR REGRESSION; NONLINEAR REGRESSION; NORMAL DISTRIBUTION; STATISTICAL SOFTWARE;

REGRESSION ANALYSIS;

MAXIMUM LIKELIHOOD; MODELLING; STATISTICAL SOFTWARE; T-DISTRIBUTION;

EID: 0031182503     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(96)00091-6     Document Type: Article

References (14)

1. Abramowitz, M. and I.A. Stegun, Handbook of mathematical functions with formulas, graphs, and mathematical Tables (National Bureau of Standards, Washington, DC, 1964).
2. Brownlee, K.A., Statistical theory and methodology in science and engineering, 2nd edn. (Wiley, New York, 1965).
3. Dempster, A.P., N.M. Laird and D.B. Rubin, Maximum likelihood estimation from incomplete data via the EM algorithm (with discussion), J. Roy. Statist. Soc. Ser. B, 39 (1977) 1-38.
4. Dempster, A.P., N.M. Laird and D.B. Rubin, Iteratively reweighted least-squares for linear regression when errors are normal/independent distributed, in: P.R. Krishnaiah (Ed.), Multivariate analysis V (North Holland, Amsterdam, 1980) 35-57.
5. Dixon, W.J. (Ed.), BMDP statistical software manual (Univ. California Press, Berkeley, 1992).
6. Draper, N. and H. Smith, Applied regression analysis, 2nd edn. (Wiley, New York, 1980).
7. Efron, B. and D.V. Hinkley, Assessing the accuracy of the maximum likelihood estimator: observed versus expected fisher information, Biometrika, 65 (1977) 457-487.
8. Jennrich, R.I., An introduction to computational statistics, regression analysis (Prentice-Hall, Englewood Cliffs, 1995).
9. Lange, K.L., R.J.A. Little and J.M.G. Taylor, Robust statistical modeling using the t distribution, J. Amer. Statist. Assoc., 84 (1989) 881-890.
10. Lange, K.L. and J.S. Sinsheimer, Normal/independent distributions and their applications in robust regression, J. Comput. Graphical Statist., 2 (1993) 175-198.
11. Liu, C. and D.B. Rubin, ML estimation of the t distribution using EM and its extensions, ECM and ECME, Statist. Sinica, 5 (1995) 19-39.
12. Luenberger, D.G., Linear and nonlinear programming, 2nd edn. (Addison-Wesley, Reading, MA, 1984).
13. Racin-Poon, A., A Bayesian approach to nonlinear calibration problems, J. Amer. Statist. Assoc., 83 (1988) 650-656.
14. Rubin, D.B., Iteratively reweighted least squares, in: Encyclopedia of statistical sciences, Vol. 4 (Wiley, New York, 1983) 272-275.