on the second-order bias of parameter estimates in nonlinear regression models with student t errors

References

• Abell , M.L. and Braselton , J.P. 1994 . “ The Maple V Handbook ” . New York AP Professional
   Google Scholar
• Anderson , J. A. and Richardson , S.C. 1979 . Logistic discrimination and bias correction in maximum likelihood estimation . Technometrics , 21 : 71 – 78 .
   Web of Science ®Google Scholar
• Cook , R. D. , Tsai , C.L. and Wei , B.C. 1986 . Bias in nonlinear regression . Biometrika , 73 : 615 – 623 .
   Web of Science ®Google Scholar
• Cordeiro , G.M. and Klein , R. 1994 . Bias correction in ARMA models . Statistics and Probability Letters , 19 : 169 – 176 .
   Web of Science ®Google Scholar
• Cordeiro , G M. and McCullagh , P. 1991 . Bias correction in generalized linear models . J. R. Statist. Soc. B , 53 : 629 – 643 .
   Google Scholar
• Cordeiro , G.M. and Vasconcellos , K.L.P. 1997 . Bias correction for a class of multivariate nonlinear regression models . Statistics and Probability Letters , 35 : 155 – 164 .
   Google Scholar
• Cox , D.R. and Hinkley , D.V. 1974 . “ Theoretical Statistics ” . London : Chapman and Hall .
   Google Scholar
• Cox , D.R. and Snell , E.J. 1968 . A general definition of residuals . J. R. Statist. Soc. B , 30 : 248 – 275 .
   Google Scholar
• Darby , S.C. and Ellis , M.J. 1976 . A test for synergism between two drugs . Appl. Statist. , 25 : 296 – 299 .
   Google Scholar
• Draper , N.R. and Smith , H. 1981 . “ Applied regression analysis ” . New York : John Wiley .
   Google Scholar
• Ferrari , S.L.P. and Arellano-Valle , R.B. 1996 . Modified likelihood ratio and score test in linear regression models using the t distribution . Braz. J. Prob. Statist. , 10 : 15 – 33 .
   Google Scholar
• Gallant , A.R. 1975 . Seemingly unrelated nonlinear regressions . Journal of Econometrics , 3 : 33 – 50 .
   Google Scholar
• Lange , K.L. , Little , R.J.A. and Taylor , J.M.G. 1989 . Robust statistical modeling using the t distribution. . J. Amer. Statist. Assoc. , 84 : 881 – 896 .
   Web of Science ®Google Scholar
• McCullagh , P. and Nelder , J.A. 1989 . “ Generalized Linear Models ” . London : Chapman and Hall .
   Google Scholar
• McLachlan , G.J. 1980 . A note on bias correction in maximum likelihood estimation with logistic discrimination . Technometrics , 22 : 621 – 627 .
   Web of Science ®Google Scholar
• Nelder , J.A. 1976 . Inverse polynomials, a useful group of multi-factor response functions . Biometrics , 22 : 128 – 141 .
   Google Scholar
• Paula , G.A. 1992 . Bias correction for exponential family nonlinear models . J. Statist. Comput. Simul. , 40 : 43 – 54 .
   Google Scholar
• Ratkowsky , D.A. 1983 . “ Nonlinear Regression Modeling ” . New York : Marcel Dekker .
   Google Scholar
• Stone , M. 1980 . J. R. Statist. Soc. B , 42 : 17 – 19 .
   Google Scholar
• Wolfram , S. 1991 . “ MATHEMATICA: a system for doing mathematics by computer ” . New York : Addison-Wesley .
   Google Scholar
• Young , D.H. and Bakir , S. T. 1987 . Bias correction for a generalized log-gamma regression model . Technometrics , 29 : 183 – 191 .
   Web of Science ®Google Scholar