A Varying Coefficients Model For Estimating Finite Population Totals: A Hierarchical Bayesian Approach

被引:1
|
作者
Velasco-Cruz, Ciro [1 ]
Fernando Contreras-Cruz, Luis [2 ]
Smith, Eric P. [3 ]
Rodriguez, Jose E. [4 ]
机构
[1] Colegio Postgrad, Stat Program, Stat, Montecillo 56230, Mexico
[2] Univ Autnoma Chapingo, Dept Fitotecn, Stat, Texcoco 56230, Mexico
[3] Virginia Tech, Dept Stat, Stat, Blacksburg, VA 24061 USA
[4] Univ Guanajuato, Math, Guanajuato, Mexico
关键词
Bayesian hierarchical model; Population total; Varying coefficient model; Auxiliary information; Nonparametric regression model; PRIOR DISTRIBUTIONS; INFERENCE;
D O I
10.1007/s13253-016-0250-9
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In some finite sampling situations, there is a primary variable that is sampled, and there are measurements on covariates for the entire population. A Bayesian hierarchical model for estimating totals for finite populations is proposed. A nonparametric linear model is assumed to explain the relationship between the dependent variable of interest and covariates. The regression coefficients in the linear model are allowed to vary as a function of a subset of covariates nonparametrically based on B-splines. The generality of this approach makes it robust and applicable to data collected using a variety of sampling techniques, provided the sample is representative of the finite population. A simulation study is carried out to evaluate the performance of the proposed model for the estimation of the population total. Results indicate accurate estimation of population totals using the approach. The modeling approach is used to estimate the total production of avocado for a large group of groves in Mexico.
引用
收藏
页码:548 / 568
页数:21
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