DOI QR코드

DOI QR Code

CERES Plot in Generalized Linear Models

  • 발행 : 2004.12.01

초록

We explore the structure and usefulness of CERES plot as a basic tool for dealing with curvature as a function of the new predictor in generalized linear models. If a predictor has a nonlinear effect and there are nonlinear relationships among the predictors, the partial residual plot and augmented partial residual plot are not able to display the correct functional form of the predictor. Unlike these plots, the CERES plot can show the correct form. This is illustrated by simulated data.

키워드

참고문헌

  1. Atkinson, A. C. (1985), Plots, Transformations, and Regression, Oxford University Press; Oxford
  2. Bandorff and Neilsen, D. E. (1978), Information and Exponential Families in Statistical Theory, Wiley; Chichester
  3. Chatterjee, S. and Hadi, A. S. (1988), Sensitivity Analysis in Linear Regression, John Wiley & Sons; New York
  4. Cook, R. D. (1993), Exploring partial residual plots, Technometrics, Vol. 35, 351-362 https://doi.org/10.2307/1270269
  5. Cook, R. D. and Weisberg, S. (1982), Residuals and influence in regression, Chapman & Hall: New York
  6. Cook, R. D. and Weisberg, S. (1999), Applied Regression Including Computing and Graphics, John Wiley and Sons, New York
  7. Ezekiel, M. (1924), A method for handling curvilinear correlation for any number of variables, Journal of the American Statistical Association, Vol. 19, 431-453 https://doi.org/10.2307/2281561
  8. Kahng, M. and Jeong, H. (2000), CERES plot in nonlinear regression, The Korean Communications in Statistics, Vol. 7, 1-11
  9. Kahng, M. and Kim, J. (1998), Partial residual plot in nonlinear regression, The Korean Communications in Statistics, Vol. 3, 571-580
  10. Mallows, C. L. (1986), Augmented partial residuals, Technometrics, Vol. 28, 313-319 https://doi.org/10.2307/1268980
  11. NeIder, J. A. and Wedderburn, R. W. M. (1972), Generalized linear models, Journal of Royal Statistical Society, A, Vol. 135, 370-384 https://doi.org/10.2307/2344614