Generating Test Data with Independently Controllable Features for Multivariate General Linear Forms

References

• Andrews , D. F. , Bickel , P. J. , Hampel , F. R. , Huber , P. J. , Rogers , W. H. and Tukey , J. W. 1972 . Robust Estimates of Location, Survey and Advances , Princeton , N.J. : Princeton University Press .
   Google Scholar
• Askin , Ronald G. and Montgomery , Douglas C. 1980 . “Augmented Robust Estimates,” . Technometrics , 22 : 333 – 341 .
   Web of Science ®Google Scholar
• Belsley , D. A. , Kuh , E. and Welsch , R. E. 1980 . Regression Diagnostics: Identifying Influential Data and Sources of Collinearity , New York : John Wiley .
   Google Scholar
• Cook , R. D. 1977 . “Detection of Influential Observations in Linear Regression,” . Technometrics , 19 : 15 – 18 .
   Web of Science ®Google Scholar
• Edelstein , Steven . 1981 . An Empirical Investigation of the Behavior of Bounded-Influence Regression Estimators , M.S. thesis Cornell University, Dept. of Economic and Social Statistics .
   Google Scholar
• Forsythe , A. B. and Moler , C. 1967 . Computer Solution of Linear Algebraic Systems , Englewood Cliffs , N.J. : Prentice Hall .
   Google Scholar
• Golub , G. H. and Reinsch , C. 1970 . “Singular Value Decomposition and Least Squares Solutions,” . Numerische Mathematik , 14 : 403 – 420 .
   Web of Science ®Google Scholar
• Hampel , F. R. 1971 . “A General Qualitative Definition of Robustness,” . The Annals of Mathematical Statistics , 42 : 1887 – 1896 .
   Google Scholar
• Heiberger , R. M. 1978 . “Generation of Random Orthogonal Matrices,” . Applied Statistics , 27 : 199 – 206 .
   Google Scholar
• Heiberger , R. M. , Velleman , P. and Ypelaar , A. “Generating Multiple Regression Test Data with Independently Controllable Features,” . Proceedings of the American Statistical Association . pp. 267 – 271 . Statistical Computing Section
   Google Scholar
• Hoaglin , D. C. and Welsch , R. E. 1978 . “The Hat Matrix in Regression and ANOVA,” . The American Statistician , 32 : 17 – 22 .
   Web of Science ®Google Scholar
• Huber , P. 1981 . Robust Statistics , New York : John Wiley .
   Google Scholar
• Krasker , W. S. and Welsch , R. E. 1982 . “Efficient Bounded-Influence Regression Estimation,” . Journal of the American Statistical Association , 77 : 595 – 604 .
   Web of Science ®Google Scholar
• Lichtenstein , D. 1981 . The Effect of Ridge Regression on High-Leverage Points in the Data , M.S. Thesis Cornell University, Dept. of Economic and Social Statistics .
   Google Scholar
• Morrison , D. F. 1976 . Multivariate Statistical Methods, , 2nd ed. , New York : McGraw-Hill .
   Google Scholar
• Mosteller , F. and Tukey , J. 1977 . Data Analysis and Regression , Reading , Mass. : Addison-Wesley .
   Google Scholar
• Seaman , J. “Use of Computer Resources by Statistical Package Regression Programs,” . Proceedings of the American Statistical Association, Statistical Computing Section . pp. 352 – 357 .
   Google Scholar
• Searle , S. R. and Firey , P. A. 1980 . “Computer Generation of Data Sets for Homework Exercises in Simple Regression,” . The American Statistician , 34 : 51 – 54 .
   Web of Science ®Google Scholar
• Stewart , G. W. 1973 . Introduction to Matrix Computations , New York : Academic Press .
   Google Scholar
• Tanner , M. and Thisted , R. 1982 . “A Remark on AS127: Generation of Random Orthogonal Matrices,” . Applied Statistics , 31 : 190 – 192 .
   Web of Science ®Google Scholar
• Tukey , J. W. 1971 . Exploratory Data Analysis , Ann Arbor , Mich. : University Microfilms . limited preliminary ed.
   Google Scholar
• Velleman , P. F. , Seaman , J. and Allen , I. E. “Evaluating Package Regression Routines,” . Proceedings of the American Statistical Association, Statistical Computing Section . pp. 82 – 92 .
   Google Scholar
• Velleman , P. F. and Welsch , R. E. 1981 . “Efficient Computing of Regression Diagnostics,” . The American Statistician , 35 : 234 – 242 .
   Web of Science ®Google Scholar
• Velleman , P. F. and Ypelaar , M. A. 1980 . “Constructing Regressions With Controlled Features: A Method of Probing Regression Performance,” . Journal of the American Statistical Association , 75 : 839 – 844 .
   Web of Science ®Google Scholar
• Welsch , R. E. and Kuh , E. 1977 . “Linear Regression Diagnostics,” , 923 – 977 . Cambridge , Mass : M.I.T. . Sloan School of Management Working Paper
   Google Scholar
• Wilkinson , J. H. 1965 . The Algebraic Eigenvalue Problem , Oxford : Clarendon Press .
   Google Scholar