Mean Square Error Matrix of an Approximate Least Squares Estimator in a Nonlinear Regression Model with Correlated Errors
نویسنده
چکیده
A nonlinear regression model with correlated, normally distributed errors is investigated. The bias and the mean square error matrix of the approximate least squares estimator of regression parameters are derived and their limit properties are studied.
منابع مشابه
Some Limit Properties of an Approximate Least Squares Estimator in a Nonlinear Regression Model with Correlated Nonzero Mean Errors
A nonlinear regression model with correlated, normally distributed errors with non zero means is investigated. The limit properties of bias and the mean square error matrix of the approximate least squares estimator of regression parameters are studied.
متن کاملWavelet Threshold Estimator of Semiparametric Regression Function with Correlated Errors
Wavelet analysis is one of the useful techniques in mathematics which is used much in statistics science recently. In this paper, in addition to introduce the wavelet transformation, the wavelet threshold estimation of semiparametric regression model with correlated errors with having Gaussian distribution is determined and the convergence ratio of estimator computed. To evaluate the wavelet th...
متن کاملA New Stochastic Restricted Biased Estimator under Heteroscedastic or Correlated Error
In this paper, under the linear regression model with heteroscedastic and/or correlated errors when the stochastic linear restrictions on the parameter vector are assumed to be held, a generalization of the ordinary mixed estimator (GOME), ordinary ridge regression estimator (GORR) and Generalized least squares estimator (GLSE) is proposed. The performance of this new estimator against GOME, GO...
متن کاملOn the Liu and Almost Unbiased Liu Estimators in the Presence of Multicollinearity with Heteroscedastic or Correlated Errors
This paper introduces a new biased estimator, namely, almost unbiased Liu estimator (AULE) of β for the multiple linear regression model with heteroscedastics and/or correlated errors and suffers from the problem of multicollinearity. The properties of the proposed estimator is discussed and the performance over the generalized least squares (GLS) estimator, ordinary ridge regression (ORR) esti...
متن کاملUsing an Efficient Penalty Method for Solving Linear Least Square Problem with Nonlinear Constraints
In this paper, we use a penalty method for solving the linear least squares problem with nonlinear constraints. In each iteration of penalty methods for solving the problem, the calculation of projected Hessian matrix is required. Given that the objective function is linear least squares, projected Hessian matrix of the penalty function consists of two parts that the exact amount of a part of i...
متن کامل