Unbiased estimation of the mean squared error of the feasible generalised ridge regression estimator

Ridge Regression Estimator: Combining Unbiased and Ordinary Ridge Regression Methods of Estimation

Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR). This estimator is obtained from unbiased ridge regression (URR) in the same way that ordinary ridge regression (ORR) is obtained from ordinary least squares (OLS). Properties of MUR are derived. Results on its matrix mean squared er...

the effects of error correction methods on pronunciation accuracy

هدف از انجام این تحقیق مشخص کردن موثرترین متد اصلاح خطا بر روی دقت آهنگ و تاکید تلفظ کلمه در زبان انگلیسی بود. این تحقیق با پیاده کردن چهار متد ارائه اصلاح خطا در چهار گروه، سه گروه آزمایشی و یک گروه تحت کنترل، انجام شد که گروه های فوق الذکر شامل دانشجویان سطح بالای متوسط کتاب اول passages بودند. گروه اول شامل 15، دوم 14، سوم 15 و آخرین 16 دانشجو بودند. دوره مربوطه به مدت 10 هفته ادامه یافت و د...

Mean-Squared Error Analysis of Kernel Regression Estimator for Time Series

Because of a lack of a priori information, the minimum mean-squared error predictor, the conditional expectation, is often not known for a non-Gaussian time series. We show that the nonparametric kernel regression estimator of the conditional expectation is mean-squared consistent for a time series: When used as a predictor, the estimator asymptotically matches the mean-squared error produced b...

The Estimation Problem of Minimum Mean Squared Error

Nonparametric estimation of mean-squared prediction error in nested-error regression models

Nested-error regression models are widely used for analyzing clustered data. For example, they are often applied to two-stage sample surveys, and in biology and econometrics. Prediction is usually the main goal of such analyses, and mean-squared prediction error is the main way in which prediction performance is measured. In this paper we suggest a new approach to estimating mean-squared predic...