Increasing Power of Robust Test through Pre-testing in Multiple Regression Model
نویسندگان
چکیده
In this paper, we define (i) unrestricted (UT), (ii) restricted (RT) and (iii) pre-test (PTT) tests for testing the significance of a subset of the parameters of a multiple regression model when the remaining parameters are (i) completely unspecified, (ii) specified at fixed values or (iii) suspected at fixed values. The M-estimation methodology is used to formulate the three tests. The asymptotic distribution of the test statistics are used to derive the asymptotic power function of the tests. Analytical and graphical comparisons of the three tests are obtained by studying the power functions with respect to the size and power of the tests. The PTT shows a reasonable dominance over the other two tests asymptotically.
منابع مشابه
Increasing power of the test through pre-test - a robust method
This paper develops robust test procedures for testing the intercept of a simple regression model when it is apriori suspected that the slope has a specified value. Defining unrestricted test (UT), restricted test (RT) and pre-test test (PTT) corresponding to the unrestricted (UE), restricted (RE), and preliminary test estimators (PTE) in the estimation case, the M-estimation methodology is use...
متن کاملRobust Estimation in Linear Regression Model: the Density Power Divergence Approach
The minimum density power divergence method provides a robust estimate in the face of a situation where the dataset includes a number of outlier data. In this study, we introduce and use a robust minimum density power divergence estimator to estimate the parameters of the linear regression model and then with some numerical examples of linear regression model, we show the robustness of this est...
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 کاملComparison of ordinary logistic regression and robust logistic regression models in modeling of pre-diabetes risk factors
Background: Regarding the increased risk of developing type 2 diabetes in pre-diabetic people, identifying pre-diabetes and determining of its risk factors seems so necessary. In this study, it is aimed to compare ordinary logistic regression and robust logistic regression models in modeling pre-diabetes risk factors. Methods: This is a cross-sectional study and conducted on 6460 people, over ...
متن کاملEVALUATION OF CONCRETE COMPRESSIVE STRENGTH USING ARTIFICIAL NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION MODELS
In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...
متن کامل