Extending the inference function for augmented margins method to implement trivariate Clayton copula-based SUR Tobit models

被引:1
作者
Ferreira, Paulo H. [1 ]
Louzada, Francisco [2 ]
机构
[1] Univ Fed Bahia, Dept Stat, BR-40110060 Salvador, BA, Brazil
[2] Univ Sao Paulo, Dept Appl Math & Stat, Sao Carlos, SP, Brazil
基金
巴西圣保罗研究基金会;
关键词
Bootstrap confidence intervals; consumption data; data augmentation; trivariate one-parameter Clayton copula; two-stage maximum likelihood estimation; ASSOCIATION; REGRESSIONS; TESTS;
D O I
10.1080/03610926.2018.1563167
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, we perform the analysis of the SUR Tobit model for three left-censored dependent variables by modeling its nonlinear dependence structure through the one-parameter Clayton copula. For unbiased parameter estimation, we propose an extension of the Inference Function for Augmented Margins (IFAM) method to the trivariate case. The interval estimation for the model parameters using resampling procedures is also discussed. We perform simulation and empirical studies, whose satisfactory results indicate the good performance of the proposed model and methods. Our procedure is illustrated using real data on consumption of food items (salad dressings, lettuce, tomato) by Americans.
引用
收藏
页码:1375 / 1401
页数:27
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