Analysis of Mixed Discrete and Continuous Classified Responses

Document Type : Original Paper

Authors

Department of Statistics, Shahid Beheshti University, Tehran, Iran

Abstract

In this paper, Our goal is classifying the responses which are mixed discrete and continuous
responses. So, first we are modeling them then get their classification rules using the Welch’s
classification rules (1939) along with their misclassification probabilities.. Also, sample classification
rules are reached using the MLE. Finally, simulation study and some real data are analyzed have
performed to show the performance of the rules.

Keywords

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[1] De Leon, A.R. and Carrière, K.C. (2007). General mixed-data model: Extension of general location and grouped continuous models. The Canadian Journal of Statistics, 35, 533 - 548. 43 تحلیل پاسخهای آمیختهی گسسته و پیوستهی ردهبندی شده [2] Welch, B.L. (1939). Note
on discriminant functions. Biometrika, 31, 218–220. [3] Tate, F.R. (1954). Correlation between discrete and continuous variables: Point-Biserial correlation. Ann. Math. Statist., 25, 603- 607. [4] Cox, D.R. and Wermuth, N. (1992). Response models for mixed
binary and quantative variables. Biometrika, 79(3), 441-461. [5] Catalano, P. and Ryan, L.M. (1992). Bivariate latent variable models for clustered discrete and continuous outcomes. Journal of the American Statistical Association, 87, 651-658. [6] De Leon, A.R., Soo, A. and Williamson, T. (2011). Classification with discrete and continuous variables via general mixed-data models. Journal of Applied Statistics, 5 (38) , 1021-1032. [7] Trivedi, P. and Zimmer, D. (2006). Copula modelling in econometrics: Introduction to practitioners. Wiley, New York. [8] Faes, C., Aerts, M., Molenberghs, G., Geys, H., Teuns, G. and Bijnes, L. (2008). A high-dimensional joint model for longitudinal outcomes of different nature. Stat. Med., 27, 4408-4427. [9] Molenberghs
, G . and Verbeke , G . (2005) . Models for Discrete Longitudinal Data. Springer-Verlag . New York . [10] Sammel, M.D. Ryan, L.M. and Legler J.M. (1997). Latent variable models for mixed discrete and continuous outcomes. Journal of the Royal Statistical
Society, B, 59, 667–678. [11] Joe , H . (1995) . Approximations multivariate normal rectangle probabilites based on conditional expectation . Journal of the American Statistical Association , 90 : 957-967. [12] Johnson, R.A. and Wichern, D.W. (2007). Applied multivariate statistical analysis. 6th ed., Prentice Hall. New York.