Influential Observations in the Functional Measurement Error Model

References

• Abdullah , M. B. 1995 . Detection of influential observations in functional errors-in-variables model . Commun-ications in Statistics: Theory and Methods , 24 ( 6 ) : 1585 – 1595 .
   Web of Science ®Google Scholar
• Aoki , R. , Achcar , J. A. , Bolfarine , H. and Singer , J. M. 2003 . Bayesian analysis of null intercept errors-in-variables regression for pretest/post-test data . Journal of Applied Statistics , 30 : 3 – 12 .
   Web of Science ®Google Scholar
• Arellano-Valle , R. B. , Galea-Rojas , M. and Iglesias , P. 2000 . Bayesian sensitivity analysis in elliptical linear regression models . Journal of Statistical Planning and Inference , 86 : 175 – 199 .
   Web of Science ®Google Scholar
• Berger , J. O. 1985 . Statistical Decision Theory and Bayesian Analysis , New York : Springer-Verlag .
   Google Scholar
• Bernardo , J. M. and Smith , A. F. M. 1994 . Bayesian Theory , Chichester : Wiley .
   Google Scholar
• Best , N. G. , Cowles , M. K. and Vines , S. K. 1997 . CODA: Convergence Diagnosis and Output Analysis Software for Gibbs sampling output: Version 0.4 , Cambridge : MRC Biostatistics Unit .
   Google Scholar
• Carrol , R. J. , Ruppert , D. and Stefanski , L. A. 1995 . Measurement Error in Nonlinear Models , London : Chapman & Hall .
   Google Scholar
• Chatterjee , S. and Hadi , A. S. 1988 . Sensivity Analysis in Linear Regression , New York : Wiley .
   Google Scholar
• Chen , M. H. , Shao , Q. M. and Ibrahim , J. G. 2000 . Monte Carlo Methods in Bayesian Computation , New York : Springer-Verlag . Springer Series in Statistics
   Google Scholar
• Cheng , C.-L. and van Ness , J. W. 1999 . Statistical Regression with Measurement Error , Vol. 6 , London : Arnold . Kendall's Library of Statistics
   Google Scholar
• Cook , R. D. 1977 . Detection of influential observations in linear regression . Technometrics , 19 : 15 – 18 .
   Web of Science ®Google Scholar
• Cook , R. D. 1987 . Influence assessment . Journal of Applied Statistics , 14 : 117 – 131 .
   Google Scholar
• Cook , R. D. and Weisberg , S. 1982 . Residuals and Influence in Regression , London : Chapman & Hall .
   Google Scholar
• Csiszár , I. 1967 . Information-type measures of difference of probability distributions and indirect observations . Studia Sci. Math. Hungar. , 2 : 299 – 318 .
   Google Scholar
• Dellaportas , P. and Stephens , D. A. 1995 . Bayesian analysis of errors in variable regression models . Biometrics , 51 : 1085 – 1095 .
   Web of Science ®Google Scholar
• Florens , J. P. , Mouchart , M. and Richard , J. F. 1974 . Bayesian inference in error-in-variables models . Journal of Multivariate Analysis , 4 : 419 – 452 .
   Google Scholar
• Fuller , W. A. 1987 . Measurement Error Models , New York : Wiley .
   Google Scholar
• Galea , M. , Bolfarine , H. and Vilca-Labra , F. 2002a . Influence diagnostics for the structural errors-in-variables model under the student-t distribution . Journal of Applied Statitics , 29 ( 8 ) : 1191 – 1204 .
   Web of Science ®Google Scholar
• Galea , M. , Bolfarine , H. and de Castro , M. 2002b . Local influence in comparative calibration models . Biometrical Journal , 41 : 59 – 81 .
   Google Scholar
• Girón , F. J. , Martínez , M. and Morcillo , C. 1992 . “ A Bayesian justification for the analysis of residual and influence measures ” . In Bayesian Statistics , Edited by: Bernardo , J. M. , Berger , J. O. , Dawid , A. P. and Smith , A. F. M. Vol. 4 , 651 – 660 . Oxford : Oxford University Press .
   Google Scholar
• Guttman , I. and Peña , D. 1988 . “ Outliers and influence: Evaluation by posteriors of parameters in the linear model ” . In Bayesian Statistics , Edited by: Bernardo , J. M. , DeGroot , M. H. , Lindley , D. V. and Smith , A. F. M. Vol. 3 , 631 – 640 . Oxford : Oxford University Press .
   Google Scholar
• Hastings , W. K. 1970 . Monte Carlo sampling methods using Markov chains and their Applications . Biometrika , 57 : 97 – 109 .
   Web of Science ®Google Scholar
• Kass , R. E. , Tierney , L. and Kadane , J. B. 1989 . Approximate methods for assessing influence and sensitivity in Bayesian analysis . Biometrika , 76 : 663 – 674 .
   Web of Science ®Google Scholar
• Kelly , G. E. 1984 . The influence function in the errors in variables problem . The Annals of Statistics , 12 : 87 – 100 .
   Web of Science ®Google Scholar
• Kempthorne , P. J. 1986 . Decision-theoretic measures of influence in regression . Journal of the Royal Statistical Society B , 48 : 370 – 378 .
   Google Scholar
• Kim , M. G. 2000 . Outliers and influential observations in the structural errors-in-variables model . Journal of Applied Statistics , 27 ( 4 ) : 451 – 460 .
   Web of Science ®Google Scholar
• Lee , A. H. and Zhao , Y. 1996 . Assessing local influence in measurement error models . Biometrical Journal , 38 : 829 – 841 .
   Web of Science ®Google Scholar
• Lindley , D. V. and El-Sayyad , G. M. 1968 . The Bayesian estimation of a linear functional relationship, Journal of Royal Statistical Society B . 30 : 190 – 202 .
   Google Scholar
• Muller , P. and Roeder , K. 1997 . A Bayesian semiparametric model for case-control studies with errors in variables . Biometrika , 84 : 523 – 537 .
   Web of Science ®Google Scholar
• O'Hagan , A. 1994 . Bayesian Inference. Kendall's Advanced Theory of Statistics , Vol. 2B , London : Edward Arnold .
   Google Scholar
• Peng , F. and Dey , D. K. 1995 . Bayesian analysis of outlier problems using divergences measures . The Canadian Journal of Statistics , 23 : 199 – 213 .
   Web of Science ®Google Scholar
• Richardson , S. 1996 . “ Measurement error ” . In Markov Chain Monte Carlo in Practice , Edited by: Gilks , W. R. , Richardson , S. and Spiegelhalter , D. I. 401 – 414 . London : Chapman & Hall .
   Google Scholar
• Robert , C. P. and Casella , G. 1999 . Monte Carlo Statistical Methods , New York : Springer-Verlag .
   Google Scholar
• Smith , A. F. M. and Roberts , G. O. 1993 . Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods . Journal of the Royal Statistical Society B , 55 : 3 – 23 .
   Google Scholar
• Villegas , C. 1972 . Bayesian inference in linear relations . Ann. Math. Statis. , 43 : 1767 – 1791 .
   Google Scholar
• Weiss , R. E. 1996 . An approach to Bayesian sensitivity analysis . Journal of the Royal Statistical Society B , 58 : 739 – 750 .
   Google Scholar
• Weiss , R. E. and Cook , R. D. 1992 . A grafical case statistic for assessing posterior influence . Biometrika , 79 : 51 – 55 .
   Web of Science ®Google Scholar
• Wellman , M. J. and Gunst , R. F. 1991 . Influence diagnostics for linear measurement error models . Biometrika , 78 ( 2 ) : 373 – 380 .
   Web of Science ®Google Scholar
• Zellner , A. 1971 . An Introduction to Bayesian Inference in Econometrics , New York : Wiley .
   Google Scholar