Spatial Beta Regression Model with Random Effect
نویسندگان
چکیده مقاله:
Abstract: In many applications we have to encountered with bounded dependent variables. Beta regression model can be used to deal with these kinds of response variables. In this paper we aim to study spatially correlated responses in the unit interval. Initially we introduce spatial beta generalized linear mixed model in which the spatial correlation is captured through a random effect. Then the performances of the proposed model is evaluated via a simulation study, implementing Bayesian approach for parameter estimation. Finally the application of this model on two real data sets about migration rate and divorce rate in Iran are presented.
منابع مشابه
A Bayesian Nominal Regression Model with Random Effects for Analysing Tehran Labor Force Survey Data
Large survey data are often accompanied by sampling weights that reflect the inequality probabilities for selecting samples in complex sampling. Sampling weights act as an expansion factor that, by scaling the subjects, turns the sample into a representative of the community. The quasi-maximum likelihood method is one of the approaches for considering sampling weights in the frequentist framewo...
متن کاملKernel Inverse Regression for Spatial Random Fields
In this paper, we propose a dimension reduction model for spatially dependent variables. Namely, we investigate an extension of the inverse regression method under strong mixing condition. This method is based on estimation of the matrix of covariance of the expectation of the explanatory given the dependent variable, called the inverse regression. Then, we study, under strong mixing condition,...
متن کاملSpatial Correlation Testing for Errors in Panel Data Regression Model
To investigate the spatial error correlation in panel regression models, various statistical hypothesizes and testings have been proposed. This paper, within introduction to spatial panel data regression model, existence of spatial error correlation and random effects is investigated by a joint Lagrange Multiplier test, which simultaneously tests their existence. For this purpose, joint Lagrang...
متن کاملBeta - Binomial and Ordinal Joint Model with Random Effects for Analyzing Mixed Longitudinal Responses
The analysis of discrete mixed responses is an important statistical issue in various sciences. Ordinal and overdispersed binomial variables are discrete. Overdispersed binomial data are a sum of correlated Bernoulli experiments with equal success probabilities. In this paper, a joint model with random effects is proposed for analyzing mixed overdispersed binomial and ordinal longitudinal respo...
متن کاملSupport vector regression with random output variable and probabilistic constraints
Support Vector Regression (SVR) solves regression problems based on the concept of Support Vector Machine (SVM). In this paper, a new model of SVR with probabilistic constraints is proposed that any of output data and bias are considered the random variables with uniform probability functions. Using the new proposed method, the optimal hyperplane regression can be obtained by solving a quadrati...
متن کاملfitting growth regression model to the boolean random sets
one of the models that can be used to study the relationship between boolean random sets and explanatory variables is growth regression model which is defined by generalization of boolean model and permitting its grains distribution to be dependent on the values of explanatory variables. this model can be used in the study of behavior of boolean random sets when their coverage regions variation...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 13 شماره 2
صفحات 215- 230
تاریخ انتشار 2017-03
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023