Showing 1 - 7 of 7
The Stein-rule (SR) and positive-part Stein-rule (PSR) estimators are two popular shrinkage techniques used in linear regression, yet very little is known about the robustness of these estimators to the disturbances' deviation from the white noise assumption. Recent studies have shown that the...
Persistent link: https://www.econbiz.de/10008521108
Sensitivity analysis stands in contrast to diagnostic testing in that sensitivity analysis aims to answer the question of whether it matters that a nuisance parameter is non-zero, whereas a diagnostic test ascertains explicitly if the nuisance parameter is different from zero. In this paper, we...
Persistent link: https://www.econbiz.de/10005006420
Consider the generalized growth curve model subject to R(Xm)[subset, double equals]...[subset, double equals]R(X1), where Bi are the matrices of unknown regression coefficients, and and are independent and identically distributed with the same first four moments as a random vector normally...
Persistent link: https://www.econbiz.de/10005221479
This paper considers the generalized growth curve model subject to R(Xm)[subset, double equals]R(Xm-1)[subset, double equals]...[subset, double equals]R(X1), where Bi are the matrices of unknown regression coefficients, Xi,Zi and U are known covariate matrices, i=1,2,...,m, and splits into a...
Persistent link: https://www.econbiz.de/10005153225
This paper derives the corrected conditional Akaike information criteria for generalized linear mixed models by analytic approximation and parametric bootstrap. The sampling variation of both fixed effects and variance component parameter estimators are accommodated in the bias correction term....
Persistent link: https://www.econbiz.de/10010665718
In this paper, we propose a combined regression estimator by using a parametric estimator and a nonparametric estimator of the regression function. The asymptotic distribution of this estimator is obtained for cases where the parametric regression model is correct, incorrect, and approximately...
Persistent link: https://www.econbiz.de/10005093869
We derive the asymptotics of the OLS estimator for a purely autoregressive spatial model. Only low-level conditions are used. As the sample size increases, the spatial matrix is assumed to approach a square-integrable function on the square (0,1)2. The asymptotic distribution is a ratio of two...
Persistent link: https://www.econbiz.de/10005221544