... Materials involving BLF will be found entirely in the work of a few statisticians such as Gil... more ... Materials involving BLF will be found entirely in the work of a few statisticians such as Giles et al. [8], Ohtani [9,10], Gruber [11], Chung et al. [12], Shalabh [13], Wan [14], Chaturvedi and Shalabh [15], Tothenburg and Shalabh [16] and Arashi [17]. ... Wang et al. ...
Communications in Statistics - Theory and Methods, 2012
ABSTRACT This article is concerned with the problem of multicollinearity in the linear part of a ... more ABSTRACT This article is concerned with the problem of multicollinearity in the linear part of a seemingly unrelated semiparametric (SUS) model. It is also suspected that some additional non stochastic linear constraints hold on the whole parameter space. In the sequel, we propose semiparametric ridge and non ridge type estimators combining the restricted least squares methods in the model under study. For practical aspects, it is assumed that the covariance matrix of error terms is unknown and thus feasible estimators are proposed and their asymptotic distributional properties are derived. Also, necessary and sufficient conditions for the superiority of the ridge-type estimator over the non ridge type estimator for selecting the ridge parameter K are derived. Lastly, a Monte Carlo simulation study is conducted to estimate the parametric and nonparametric parts. In this regard, kernel smoothing and cross validation methods for estimating the nonparametric function are used.
... Materials involving BLF will be found entirely in the work of a few statisticians such as Gil... more ... Materials involving BLF will be found entirely in the work of a few statisticians such as Giles et al. [8], Ohtani [9,10], Gruber [11], Chung et al. [12], Shalabh [13], Wan [14], Chaturvedi and Shalabh [15], Tothenburg and Shalabh [16] and Arashi [17]. ... Wang et al. ...
Communications in Statistics - Theory and Methods, 2012
ABSTRACT This article is concerned with the problem of multicollinearity in the linear part of a ... more ABSTRACT This article is concerned with the problem of multicollinearity in the linear part of a seemingly unrelated semiparametric (SUS) model. It is also suspected that some additional non stochastic linear constraints hold on the whole parameter space. In the sequel, we propose semiparametric ridge and non ridge type estimators combining the restricted least squares methods in the model under study. For practical aspects, it is assumed that the covariance matrix of error terms is unknown and thus feasible estimators are proposed and their asymptotic distributional properties are derived. Also, necessary and sufficient conditions for the superiority of the ridge-type estimator over the non ridge type estimator for selecting the ridge parameter K are derived. Lastly, a Monte Carlo simulation study is conducted to estimate the parametric and nonparametric parts. In this regard, kernel smoothing and cross validation methods for estimating the nonparametric function are used.
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