The Acceptability of Regression Solutions: Another Look at Computational Accuracy

Autor:	Albert E. Beaton, John L. Barone, Donald B. Rubin
Rok vydání:	1976
Předmět:	Statistics and Probability Set (abstract data type) Computational model Mathematical optimization Index (economics) Mathematical model Computer science Computation Statistics Linear regression Regression analysis Statistics Probability and Uncertainty Regression
Zdroj:	Journal of the American Statistical Association. 71:158-168
ISSN:	1537-274X 0162-1459
DOI:	10.1080/01621459.1976.10481507
Popis:	Longley proposed a set of data for use in testing regression programs. This paper shows that the numerically accurate solution is likely to be an unreasonable estimate of the regression coefficients for this problem. This is true because the accuracy of the data and appropriateness of the model may affect the solution more than the computational method. An easily computed index is derived that can be used to indicate such computational instability. The basic conclusion is that a concern about highly accurate computational methods must be tempered with a concern for whether the data are accurate enough to make the results of such computation meaningful.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::649fab611a6e4a03ecaa5cb840812d3a https://doi.org/10.1080/01621459.1976.10481507 Zobrazit plný text záznamu