ESTIMATION OF PARAMETERS OF THE SIMPLE MULTIVARIATE LINEAR MODEL WITH STUDENT-t ERRORS
نویسنده
چکیده
This paper considers estimation of the intercept and slope vector parameters of the simple multivariate linear regression model with Student-t errors in the presence of uncertain prior information on the value of the unknown slope vector. The unrestricted, restricted, preliminary test, shrinkage, and positive-rule shrinkage estimators are defined together with the expressions for the bias, quadratic bias, quadratic risk and mean squared errors (mse) functions of the estimators are derived. Comparison of the estimators is made using quadratic risk criterion. Based on the study we conclude that for p ≥ 3 shrinkage estimators are recommended, and for p ≤ 2, the preliminary test estimators are preferable.
منابع مشابه
Phase II monitoring of multivariate simple linear profiles with estimated parameters
In some applications of statistical process monitoring, a quality characteristic can be characterized by linear regression relationships between several response variables and one explanatory variable, which is referred to as a “multivariate simple linear profile.” It is usually assumed that the process parameters are known in Phase II. However, in most applications, this assumption is viola...
متن کاملModeling of temperature in friction stir welding of duplex stainless steel using multivariate lagrangian methods, linear extrapolation and multiple linear regression
In this study, the temperature in friction stir welding of duplex stainless steel has been investigated. At first, temperature estimation was modeled and estimated at different distances from the center of the stir zone by the multivariate Lagrangian function. Then, the linear extrapolation method and multiple linear regression method were used to estimate the temperature outside the range and ...
متن کاملModeling of temperature in friction stir welding of duplex stainless steel using multivariate lagrangian methods, linear extrapolation and multiple linear regression
In this study, the temperature in friction stir welding of duplex stainless steel has been investigated. At first, temperature estimation was modeled and estimated at different distances from the center of the stir zone by the multivariate Lagrangian function. Then, the linear extrapolation method and multiple linear regression method were used to estimate the temperature outside the range and ...
متن کاملESTIMATING THE PARAMETERS OF A FUZZY LINEAR REGRESSION MODEL
Fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. Several methods for evaluating fuzzy coefficients in linear regression models have been proposed. The first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. In this the...
متن کاملPerformance evaluation of different estimation methods for missing rainfall data
There are numerous methods to estimate missing values of which some are used depending on the data type and regional climatic characteristics. In this research, part of the monthly precipitation data in Sarab synoptic station, east Azerbaijan province, Iran was randomly considered missing values. In order to study the effectiveness of various methods to estimate missing data, by seven classic s...
متن کامل