Simulation Analysis Of Regression Estimators Based On Coefficients of Uncertainty
نویسنده
چکیده
The paper is devoted to the problem of incorporating prior information in the regression analysis. Some indices of uncertainty of the prior knowledge are proposed and their usefulness is studied. To incorporate prior information together with its uncertainty into regression estimation some coefficients of uncertainty are introduced as well. Performance of estimators based upon proposed descriptions of uncertainty is examined via computer simulations.
منابع مشابه
Liu Estimates and Influence Analysis in Regression Models with Stochastic Linear Restrictions and AR (1) Errors
In the linear regression models with AR (1) error structure when collinearity exists, stochastic linear restrictions or modifications of biased estimators (including Liu estimators) can be used to reduce the estimated variance of the regression coefficients estimates. In this paper, the combination of the biased Liu estimator and stochastic linear restrictions estimator is considered to overcom...
متن کاملDifferenced-Based Double Shrinking in Partial Linear Models
Partial linear model is very flexible when the relation between the covariates and responses, either parametric and nonparametric. However, estimation of the regression coefficients is challenging since one must also estimate the nonparametric component simultaneously. As a remedy, the differencing approach, to eliminate the nonparametric component and estimate the regression coefficients, can ...
متن کاملSpeech Enhancement using Laplacian Mixture Model under Signal Presence Uncertainty
In this paper an estimator for speech enhancement based on Laplacian Mixture Model has been proposed. The proposed method, estimates the complex DFT coefficients of clean speech from noisy speech using the MMSE estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of noise are assumed zero-mean Gaussian distribution. Furthermore, the MMS...
متن کاملGeneralized Ridge Regression Estimator in Semiparametric Regression Models
In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...
متن کاملUsing SWAT and SWAT-CUP for hydrological simulation and uncertainty analysis in arid and semi-arid watersheds (Case study: Zoshk Watershed, Shandiz, Iran)
The aims of this project was to assess the capability of SWAT model and SWAT-CUP software in hydrological simulation and to evaluate the uncertainty of SWAT model in estimating runoff in arid and semi-arid watersheds. Model calibration and uncertainty analysis were performed using the Sequential Uncertainty Fitting (SUFI2) algorithm. In the stage of calibration and validation of water flow, per...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000