Scan Statistics for Detecting a Local Change in Variance for Normal Data with Known Variance
Autor: | Joseph Glaz, Bo Zhao |
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Rok vydání: | 2015 |
Předmět: |
Statistics and Probability
PRESS statistic 010504 meteorology & atmospheric sciences Scan statistic General Mathematics Physics::Medical Physics Explained sum of squares Window (computing) Variance (accounting) 01 natural sciences 010104 statistics & probability Likelihood-ratio test Ancillary statistic Statistics 0101 mathematics Statistic 0105 earth and related environmental sciences Mathematics |
Zdroj: | Methodology and Computing in Applied Probability. 18:563-573 |
ISSN: | 1573-7713 1387-5841 |
Popis: | In this article, several scan statistics are discussed for detecting a local change in variance for one dimensional normal data. When the length of the scanning window is known, a fixed window scan statistic based on moving sum of squares is proposed. Two approximations for the distribution of this scan statistic are investigated. When the length of the scanning window is unknown, a variable window scan statistic based on a generalized likelihood ratio test and a multiple window minimum P-value scan statistic are proposed for detecting the local change in variance. For a moderate or large shift in variance, numerical results indicate that both the variable and multiple window scan statistics perform well. For large data sets, considering the detection power and computing efficiency, the multiple window scan statistic is recommended. |
Databáze: | OpenAIRE |
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