Skewed Error Research Articles

Detecting Skewed Errors from Regression Residuals

Symmetry of the error distribution is a common assumption in robust estimation of location and regression parameters. Tests for detecting asymmetry in the location problem are available, but their performance in regression situations is unknown. Here two such tests are investigated, and the evidence suggests two conclusions. First, the tests are valid when applied directly to either robust or least squares residuals as long as the number of parameters estimated is no more than a fourth of the sample size. Second, the effect of the design matrix on power for detecting a skewed error distribution is roughly characterized by a third-moment quantity based on least squares analysis.

Detecting Skewed Errors From Regression Residuals

Symmetry of the error distribution is a common assumption in robust estimation of location and regression parameters. Tests for detecting asymmetry in the location problem are available, but their performance in regression situations is unknown. Here two such tests are investigated, and the evidence suggests two conclusions. First, the tests are valid when applied directly to either robust or least squares residuals as long as the number of parameters estimated is no more than a fourth of the sample size. Second, the effect of the design matrix on power for detecting a skewed error distribution is roughly characterized by a third-moment quantity based on least squares analysis.

Skewness and Data Errors: An Australian Replication

The possibility of errors exists in all data bases although checks are usually wade to find and eliminate them. Beedles and Simkowitz identified potential errors in recording prices of New York Stock Exchange securities by studying their measured relative skewness. A similar procedure is applied to Brown's file of Melbourne share returns, with the results indicating that it is virtually error free.

A Note on Skewness and Data Errors

The Journal of FinanceVolume 33, Issue 1 p. 288-292 Note A NOTE ON SKEWNESS AND DATA ERRORS William L. Beedles, William L. BeedlesSearch for more papers by this authorMichael A. Simkowitz, Michael A. SimkowitzThe authors are, respectively, Assistant and Associate Professors of Finance, Indiana University, Bloomington. While retaining responsibility for errors, the authors wish to thank Richard McEnally for helpful comments on the earlier draft.Search for more papers by this author William L. Beedles, William L. BeedlesSearch for more papers by this authorMichael A. Simkowitz, Michael A. SimkowitzThe authors are, respectively, Assistant and Associate Professors of Finance, Indiana University, Bloomington. While retaining responsibility for errors, the authors wish to thank Richard McEnally for helpful comments on the earlier draft.Search for more papers by this author First published: March 1978 https://doi.org/10.1111/j.1540-6261.1978.tb03405.xCitations: 13 Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume33, Issue1March 1978Pages 288-292 RelatedInformation

Reduction of error rates in the microlymphocytotoxicity test.

The overall error rate of the microlymphocytotoxicity test has been reduced from 1.08% in 1971 to approximately 0.35%, based on comparisons of 882 replicate test pairs (different bleedings) and on family studies, with 0.11% attributable to "reading" errors. This reduction was attributed to automation for lymphocyte adding, better incubation temperature control, better technical preparation of cells and stronger, more monospecific sera. Three types of errors contribute to the overall error rate: random, sera-related (affected by strength and specificity), and lymphocyte-related (possible B-cell reactivity and donor/lymphocyte physiological condition). Strongly skewed error distributions, which seem to be lymphocyte-related, occurred in less than 4% of the test pairs.