Showing papers on "Outlier published in 1973"
TL;DR: In this article, a procedure of studentizing or standardizing the residuals by dividing them by their estimated standard deviations is proposed for testing for outliers in simple linear regression, and it is shown that these values are extremely close to the values in Grubbs' (1950) Table IA and independent of the values taken for the independent variable.
Abstract: A procedure of studentizing or standardizing the residuals by dividing them by their estimated standard deviations is proposed for testing for outliers in simple linear regression. A simulation study yielded the critical values of the test statistic, and it is shown that these values are extremely close to the values in Grubbs' (1950) Table IA and independent of the values taken for the independent variable.
65 citations
TL;DR: In this article, the type I error probabilities when a single outlier test is applied repeatedly to a sample were investigated. And expressions for the power loss due to masking were derived for the case when multiple outliers are present.
Abstract: Summary The paper deals with the type I error probabilities when a single outlier test is applied repeatedly to a sample In the case in which multiple outliers are present, expressions for the power loss due to masking are derived
8 citations
TL;DR: In this article, the problem of detecting outliers or "wild" values within replicate sets of three measurements is discussed, where the statistics discussed are useful for monitoring X-ray data, particularly in computer oriented systems.
Abstract: On the assumption that X-ray count data are normally distributed, certain tests for detecting outliers or ‘wild’ values within replicate sets of three measurements are compared. Treated as ‘insurance policies’ rather than formal statistical tests, the statistics discussed are useful for monitoring X-ray data, particularly in computer oriented systems. The problem of the correction of outliers is briefly discussed.
2 citations
TL;DR: In this paper, the authors considered the problem of estimating the mean and variance of the population yielding the other observations, and developed unbiased estimates that are unbiased if terms of ordern ≥ −1+A +2 ǫ are neglected.
Abstract: The data (continuous) aren independent observations that are believed to be a random sample. The possibility exists, however, that as many asJ of the largest observations, and as many asK of the smallest observations, are outliers. That is, these observations are from populations that are different from the population yielding the other observations (which number at leastn−J−K). The interest is in obtaining suitable estimates for the mean and variance of the population yielding the other observations.J andK are given and relatively small, with both ≦2n
A
, whereA is specified and ≦1/4. When the population yielding the other observations is continuous, has moments of all orders, and is well-behaved in some other ways, estimates are developed that are unbiased if terms of ordern
−1+A
+2ɛ are neglected. Here, ɛ can be arbitrarily small but is positive.
1 citations