Further properties and new applications of the nested Dirichlet distribution

Recently, Ng et al. (2009) studied a new family of distributions, namely the nested Dirichlet distributions. This family includes the traditional Dirichlet distribution as a special member and can be adopted to analyze incomplete categorical data. However, other important aspects of the family, such as marginal and conditional distributions and related properties are not yet available in the literature. Moreover, diverse applications of the family to the real world need to be further explored. In this paper, we first obtain the marginal and conditional distributions and other related properties of the nested Dirichlet distribution. We then present new applications of the family in fitting competing-risks model, analyzing incomplete categorical data and evaluating cancer diagnosis tests. Three real data involving failure times of radio transmitter receivers, attitude toward the death penalty and ultrasound ratings for breast cancer metastasis are provided.

[1]  I. Olkin,et al.  Inequalities: Theory of Majorization and Its Applications , 1980 .

[2]  Rameshwar D. Gupta,et al.  The History of the Dirichlet and Liouville Distributions , 2001 .

[3]  ESTIMATION OF PARAMETERS OF MIXED EXPONENTIALLY DISTRIBUTED FAILURE TIME DISTRIBUTIONS FROM CENSORED LIFE TEST DATA , 1958 .

[4]  Tim Robertson,et al.  Restricted tests for testing independence of time to failure and cause of failure in a competing-risks model , 1998 .

[5]  Guo-Liang Tian,et al.  Bayesian computation for contingency tables with incomplete cell-counts , 2003 .

[6]  D. Cox,et al.  THE ANALYSIS OF EXPONENTIALLY DISTRIBUTED LIFE-TIMES WITH Two TYPES OF FAILURE , 1959 .

[7]  M. Pepe The Statistical Evaluation of Medical Tests for Classification and Prediction , 2003 .

[8]  V T Farewell,et al.  The analysis of failure times in the presence of competing risks. , 1978, Biometrics.

[9]  Man-Lai Tang,et al.  On improved EM algorithm and confidence interval construction for incomplete r , 2007, Comput. Stat. Data Anal..

[10]  R. Dykstra,et al.  Statistical inference for uniform stochastic ordering in several populations , 1991 .

[11]  N. Balakrishnan,et al.  A Primer on Statistical Distributions , 2003 .

[12]  B. D. Sivazlian On a Multivariate Extension of the Gamma and Beta Distributions , 1981 .

[13]  Lyle D. Broemeling,et al.  Bayesian Biostatistics and Diagnostic Medicine , 2007 .

[14]  P C Lambert,et al.  A Bayesian Approach to a General Regression Model for ROC Curves , 1998, Medical decision making : an international journal of the Society for Medical Decision Making.

[15]  Joseph B. Kadane,et al.  Juries Hearing Death Penalty Cases: Statistical Analysis of a Legal Procedure , 1983 .

[16]  Joseph Edwards A Treatise On The Integral Calculus,vol.1 , 1921 .

[17]  D. Rubin INFERENCE AND MISSING DATA , 1975 .

[18]  B. D. Sivazlian A Class of Multivariate Distributions , 1981 .

[19]  R. A. Roberts,et al.  A Treatise on the Integral Calculus , 2009 .

[20]  Donald St. P. Richards,et al.  The Dirichlet distributions and polynomial regression , 1990 .

[21]  Samuel Kotz,et al.  Multivariate Liouville Distributions , 2005 .

[22]  THE NESTED DIRICHLET DISTRIBUTION AND INCOMPLETE CATEGORICAL DATA ANALYSIS , 2009 .

[23]  Joseph B. Kadane,et al.  Bayesian Methods for Censored Categorical Data , 1987 .

[24]  S. Kotz,et al.  Symmetric Multivariate and Related Distributions , 1989 .

[25]  Donald St. P. Richards,et al.  Multivariate Liouville distributions, III , 1987 .

[26]  Xiao-Hua Zhou,et al.  Statistical Methods in Diagnostic Medicine , 2002 .

[27]  Man-Lai Tang,et al.  Grouped Dirichlet distribution: A new tool for incomplete categorical data analysis , 2008 .

[28]  Fengchun Peng,et al.  Bayesian Analysis of ROC Curves Using Markov-chain Monte Carlo Methods , 1996, Medical decision making : an international journal of the Society for Medical Decision Making.