## ⓘ Truncation (statistics)

In statistics, truncation results in values that are limited above or below, resulting in a truncated sample. A random variable y {\displaystyle y} is said to be truncated from below if, for some threshold value c {\displaystyle c}, the exact value of y {\displaystyle y} is known for all cases y > c {\displaystyle y> c}, but unknown for all cases y ≤ c {\displaystyle y\leq c}. Similarly, truncation from above means the exact value of y {\displaystyle y} is known in cases where y < c {\displaystyle y

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Popovicius inequality on variances |

Probability integral transform |

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Shape of a probability distribution |

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Stability (probability) |

Tail dependence |

Truncated distribution |

Zero bias transform |

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