Comparison of Estimates on Covariance Matrix
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Abstract
For linear regression models with heteroscedastical errors, this paper compares the estimates of covariance matrix on the least square estimate of regression coefficiencies by computer simulation. Our research shows that when sample size is greater than 50, the least square estimate of regression coefficiencies has high estimate precision. Among five estimates of its covariance, that of the ordinary least squares estimate is the best.
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