Why cannot we have a strongly consistent family of skew normal (And higher order) distributions
© Springer International Publishing AG 2017. In many practical situations, the only information that we have about the probability distribution is its first few moments. Since many statistical techniques requires us to select a single distribution, it is therefore desirable to select, out of all pos...
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th-cmuir.6653943832-407892017-09-28T04:11:25Z Why cannot we have a strongly consistent family of skew normal (And higher order) distributions Dumrongpokaphan T. Kreinovich V. © Springer International Publishing AG 2017. In many practical situations, the only information that we have about the probability distribution is its first few moments. Since many statistical techniques requires us to select a single distribution, it is therefore desirable to select, out of all possible distributions with these moments, a single “most representative” one. When we know the first two moments, a natural idea is to select a normal distribution. This selection is strongly consistent in the sense that if a random variable is a sum of several independent ones, then selecting normal distribution for all of the terms in the sum leads to a similar normal distribution for the sum. In situations when we know three moments, there is also a widely used selection—of the so-called skew-normal distribution. However, this selection is not strongly consistent in the above sense. In this paper, we show that this absence of strong consistency is not a fault of a specific selection but a general feature of the problem: for third and higher order moments, no strongly consistent selection is possible. 2017-09-28T04:11:25Z 2017-09-28T04:11:25Z Book Series 1860949X 2-s2.0-85012925157 10.1007/978-3-319-50742-2_4 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012925157&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/40789 |
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© Springer International Publishing AG 2017. In many practical situations, the only information that we have about the probability distribution is its first few moments. Since many statistical techniques requires us to select a single distribution, it is therefore desirable to select, out of all possible distributions with these moments, a single “most representative” one. When we know the first two moments, a natural idea is to select a normal distribution. This selection is strongly consistent in the sense that if a random variable is a sum of several independent ones, then selecting normal distribution for all of the terms in the sum leads to a similar normal distribution for the sum. In situations when we know three moments, there is also a widely used selection—of the so-called skew-normal distribution. However, this selection is not strongly consistent in the above sense. In this paper, we show that this absence of strong consistency is not a fault of a specific selection but a general feature of the problem: for third and higher order moments, no strongly consistent selection is possible. |
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Dumrongpokaphan T. Kreinovich V. |
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Dumrongpokaphan T. Kreinovich V. Why cannot we have a strongly consistent family of skew normal (And higher order) distributions |
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Dumrongpokaphan T. Kreinovich V. |
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Dumrongpokaphan T. |
title |
Why cannot we have a strongly consistent family of skew normal (And higher order) distributions |
title_short |
Why cannot we have a strongly consistent family of skew normal (And higher order) distributions |
title_full |
Why cannot we have a strongly consistent family of skew normal (And higher order) distributions |
title_fullStr |
Why cannot we have a strongly consistent family of skew normal (And higher order) distributions |
title_full_unstemmed |
Why cannot we have a strongly consistent family of skew normal (And higher order) distributions |
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why cannot we have a strongly consistent family of skew normal (and higher order) distributions |
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2017 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012925157&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/40789 |
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