Bias and mean squared error of the slope estimator in a regression with not necessarily normal errors in both variables

Autor:	V. K. Srivastava, H. Schneeweiss
Rok vydání:	1994
Předmět:	Statistics and Probability Bias of an estimator Mean squared error Bessel's correction Linear regression Statistics Estimator Errors-in-variables models Regression analysis Statistics Probability and Uncertainty Nonlinear regression Mathematics
Zdroj:	Statistical Papers. 35:329-335
ISSN:	1613-9798 0932-5026
DOI:	10.1007/bf02926425
Popis:	The least squares estimation of the slope parameter of a simple linear regression is biased if the regressor variable is measured with random errors. This bias as well as the mean squared error is computed up to the order of 1/T without assuming normality for the error variable. They depend on the fourth moment of the error variable.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6c50cec82733f500c6d73d863d32a228 https://doi.org/10.1007/bf02926425 Zobrazit plný text záznamu Full text from SpringerLink