Inference for general parametric functions in Box-Cox-type transformation models

Canadian Journal of Statistics

Volumn 36, Issue 2, 2008, Pages 301-319

  Yang, Zhenlin ^a   Wu, Eden Ka Ho ^b   Desmond, Anthony F ^c  

^a SINGAPORE MANAGEMENT UNIVERSITY   (Singapore)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^c UNIVERSITY OF GUELPH   (Canada)

Author keywords

Box Cox transformation; Confidence interval; Marginal effect; Percentile function; Robustness; Survivor function; Test; Variance inflation factor

Indexed keywords

EID: 47949115422     PISSN: 03195724     EISSN: None     Source Type: Journal    
DOI: 10.1002/cjs.5550360208     Document Type: Article

References (24)

1. P. J. Bickel & K. A. Doksum (1981). An analysis of transformations revisited. Journal of the American Statistical Association, 76, 296-311.
2. G. E. P. Box & D. R. Cox (1964). An analysis of transformations (with discussion). Journal of the Royal Statistical Society Series B, 26, 211-252.
3. G. E. P. Box & D. R. Cox (1982). An analysis of transformations revisited, rebutted. Journal of the American Statistical Association, 77, 209-210.
4. J. B. Burbidge, L. Magee & A. L. Robb (1988). Alternative transformations to handle extreme values of the dependent variable. Journal of the American Statistical Association, 83, 123-127.
5. R. J. Carroll (1982). Tests for regression parameters in power transformation models. Scandinavian Journal of Statistics, 9, 217-222.
6. R. J. Carroll & D. Ruppert (1984). Power transformations when fitting theoretical models to data. Journal of the American Statistical Association, 79, 321-328
7. R. J. Carroll & D. Ruppert (1988). Transformation and Weighting in Regression. Chapman & Hall, London.
8. S. Chatterjee & A. S. Hadi (2006). Regression Analysis by Example. Wiley, Hoboken, New Jersey.
9. G. Chen, R. A. Lockhart & M. A. Stephens (2002). Box-Cox transformations in linear models: large sample theory and tests of normality (with discussion). The Canadian Journal of Statistics, 30, 177-234.
10. A. M. Foster, L. Tian & L. J. Wei (2001). Estimation for the Box-Cox transformation model without assuming parametric error distribution. Journal of the American Statistical Association, 96, 1097-1101.
11. G. J. Hahn & W. Q. Meeker (1991). Statistical Intervals, A Guide for Practitioners. Wiley, New York.
12. F. Hernandez & R. A. Johnson (1980). The large-sample behavior of transformations to normality. Journal of the American Statistical Association, 75, 855-861.
13. D. V. Hinkley & G. Runger (1984). The analysis of transformed data. Journal of the American Statistical Association, 79, 302-320.
14. P. M. Hooper & Z. L. Yang (1997). Confidence intervals following Box-Cox transformation. The Canadian Journal of Statistics, 25, 401-416.
15. J. A. John & N. A. Draper (1980). An alternative family of transformations. Applied Statistics, 29, 190-197.
16. J. G. MacKinnon & L. Magee (1990). Transforming the dependent variable in regression models. International Economic Review, 31, 315-339.
17. B. F. Manly (1976). Exponential data transformation. The Statistician, 25, 37-42.
18. W. M. Patefield (1977). On the maximized likelihood function. Sankhyā, Series B, 39, 92-96.
19. H. White (1994). Estimation, Inference and Specification Tests. Cambridge University Press.
20. Z. L. Yang (1999). Estimating a transformation and its effect on Box-Cox T-ratio. Test, 8, 167-190.
21. Z. L. Yang (2002a). Comment on "Box-Cox transformations in linear models: large sample theory and tests of normality." The Canadian Journal of Statistics, 30, 222-225.
22. Z. L. Yang (2002b). Median estimation through a regression transformation. The Canadian Journal of Statistics, 30, 235-242.
23. Z. L. Yang (2006). A modified family of power transformations. Economics Letters, 92, 14-19.
24. I. K. Yeo & R. A. Johnson (2000). A new family of power transformation to improve normality or symmetry. Biometrika, 87, 954-959.