A Generalized Additive Model for Discrete-Choice Data

REFERENCES

• Abe , M. 1995 . “A Nonparametric Density Estimation Method for Brand Choice Using Scanner Data,” . Marketing Science , 14 : 300 – 325 .
   Google Scholar
• Ben-Akiva , M. and Lerman , S. 1985 . Discrete Choice Analysis: Theory and Application to Travel Demand , Cambridge , MA : MIT Press .
   Google Scholar
• Blattberg , R. C. , Briesch , R. and Fox , E. 1995 . “How Promotions Work,” . Marketing Science , 14 : G122 – G133 .
   Web of Science ®Google Scholar
• Breiman , L. and Friedman , J. H. 1985 . “Estimating Optimal Transformations for Multiple Regression and Correlation,” . Journal of the American Statistical Association , 80 : 580 – 619 .
   Web of Science ®Google Scholar
• Breslow , N. S. and Day , N. E. 1980 . Statistical Methods in Cancer Research. 1: The Analysis of Case-Control Studies , Lyon : International Agency for Research on Cancer, I.A.R.C. .
   Google Scholar
• Briesch , R. A. , Chintagunta , P. K. and Matzkin , R. L. 1997 . “Nonparametric and Semiparametric Models of Brand Choice Behavior,” , The University of Texas at Austin, Dept, of Management Science and Information Systems . working paper
   Google Scholar
• Fader , P. S. , Lattin , J. M. and Little , J. D. C. 1992 . “Estimating Nonlinear Parameters in the Multinomial Logit Model,” . Marketing Science , 11 : 372 – 385 .
   Web of Science ®Google Scholar
• Friedman , J. H. and Stuetzle , W. 1981 . “Projection Pursuit Regression,” . Journal of the American Statistical Association , 76 : 817 – 823 .
   Web of Science ®Google Scholar
• Guadagni , P. M. and Little , J. D. C. 1983 . “A Logit Model of Brand Choice Calibrated on Scanner Data,” . Marketing Science , 2 : 203 – 238 .
   Google Scholar
• Gupta , S. and Cooper , L. G. 1992 . “The Discounting of Discounts and Promotion Thresholds (by Consumers),” . Journal of Consumer Research , 19 : 401 – 411 .
   Web of Science ®Google Scholar
• Hastie , T. and Tibshirani , R. 1986 . “Generalized Additive Models,” . Statistical Science , 1 : 297 – 318 .
   Google Scholar
• Hastie , T. and Tibshirani , R. 1987 . “Generalized Additive Models: Some Applications,” . Journal of the American Statistical Association , 82 : 371 – 386 .
   Web of Science ®Google Scholar
• Hastie , T. and Tibshirani , R. 1990 . Generalized Additive Models , New York : Chapman and Hall .
   Google Scholar
• Horowitz , J. L. , Bolduc , D. , Divankar , S. , Geweke , J. , Gonul , F. , Hajivassiliou , V. , Koppelman , F. S. , Kean , M. , Matzkin , R. , Rossi , P. and Ruud , P. 1994 . “Advances in Random Utility Models: Report of the Workshop on Advances in Random Utility Models,” . Marketing Letters , 5 : 311 – 322 .
   Google Scholar
• Hosmer , D. W. and Lemeshow , S. 1989 . Applied Logistic Regression , New York : Wiley .
   Google Scholar
• Kahneman , D. and Tversky , A. 1979 . “A Prospect Theory: An Analysis of Decision Under Risk,” . Econometrica , 47 : 263 – 291 .
   Google Scholar
• Kalyanaram , G. and Little , J. D. C. 1994 . “An Empirical Analysis of Latitude of Price Acceptance in Consumer Packaged Goods,” . Journal of Consumer Research , 21 : 408 – 418 .
   Web of Science ®Google Scholar
• Krishnamurthi , L. and Raj , S. P. 1988 . “A Model of Brand Choice and Purchase Quantity Price Sensitivities,” . Marketing Science , 7 : 1 – 20 .
   Web of Science ®Google Scholar
• Landwehr , J. M. , Pregibon , D. and Shoemaker , A. C. 1984 . “Graphical Methods for Assessing Logistic Regression Models,” . Journal of the American Statistical Association , 79 : 61 – 71 .
   Web of Science ®Google Scholar
• Manski , C. F. 1975 . “Maximum Score Estimation of the Stochastic Utility Model of Choice,” . Journal of Econometrics , 3 : 205 – 228 .
   Google Scholar
• Manski , C. F. and McFadden , D. , eds. 1981 . Structural Analysis of Discrete Data With Econometric Applications , Cambridge , MA : MIT Press .
   Google Scholar
• Matzkin , R. L. 1993 . “Nonparametric Identification and Estimation of Polychotomous Choice Models,” . Journal of Econometrics , 58 : 137 – 168 .
   Web of Science ®Google Scholar
• McFadden , D. 1974 . “Conditional Logit Analysis of Qualitative Choice Behavior,” . In Frontiers in Econometrics , Edited by: Zarembka , P. 105 – 142 . New York : Academic Press .
   Google Scholar
• McFadden , D. 1989 . “A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration,” . Econometrica , 57 : 995 – 1026 .
   Web of Science ®Google Scholar
• Monroe , K. B. 1973 . “Buyers' Subjective Perceptions of Price,” . Journal of Marketing Research , 10 : 70 – 80 .
   Web of Science ®Google Scholar
• Monroe , K. B. 1990 . Pricing: Making Profitable Decisions , New York : McGraw-Hill .
   Google Scholar
• Nelder , J. A. and Wedderburn , R. W. M. 1972 . “Generalized Linear Models,” . Journal of the Royal Statistical Society, Ser. A , 135 : 370 – 384 .
   Google Scholar
• Pedrick , J. H. and Zufryden , F. S. 1991 . “Evaluating the Impact of Advertising Media Plans: A Model of Consumer Purchase Dynamics Using Single-Source Data,” . Marketing Science , 10 : 111 – 130 .
   Web of Science ®Google Scholar
• Silverman , B. W. 1986 . Density Estimation for Statistics and Data Analysis (Monographs on Statistics and Applied Probability) , New York : Chapman and Hall .
   Google Scholar
• Tellis , G. J. 1988 . “Advertising Exposure, Loyalty, and Brand Purchase: A Two-Stage Model of Choice,” . Journal of Marketing Research , 25 : 134 – 144 .
   Web of Science ®Google Scholar