A statistical test for the mean squared error

Autor:	Poul Thyregod, Erik Holst
Rok vydání:	1999
Předmět:	Statistics and Probability Observational error Mean squared error Applied Mathematics Normal distribution Modeling and Simulation Likelihood-ratio test Bessel's correction Statistics Chi-square test Test statistic Null distribution Statistics Probability and Uncertainty Mathematics
Zdroj:	Journal of Statistical Computation and Simulation. 63:321-347
ISSN:	1563-5163 0094-9655
DOI:	10.1080/00949659908811960
Popis:	The likelihood ratio test for a specified value of the mean squared error is derived assuming observation from a normal distribution. The mean squared error is a well established tool for assessing closeness to a target value when bias as well as sampling error (or measurement error) is taken into account. While the distributional properties of the mean squared error are well known, so far no simple tests for hypotheses concerning the MSE have been established. An explicit expression for the likelihood ratio test statistic is provided together with a simple intuitive interpretation. The distribution of the test statistic under the null-hypothesis is discussed and it is shown that the specified value of the MSE enters as a scale-parameter. This means that it is only necessary to determine the distribution of the test-statistic when the hypothesized MSE equals one. In principle, the null distribution of the test-statistic depends on the partition of the MSE into the bias component and the variance. However,...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::724d677885868caff1263bc0ccbb0b57 https://doi.org/10.1080/00949659908811960 Zobrazit plný text záznamu