Английская Википедия:Group family

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In probability theory, especially as that field is used in statistics, a group family of probability distributions is a family obtained by subjecting a random variable with a fixed distribution to a suitable family of transformations such as a location-scale family, or otherwise a family of probability distributions acted upon by a group.[1]

Consideration of a particular family of distributions as a group family can, in statistical theory, lead to the identification of an ancillary statistic.[2]

Types of group families

A group family can be generated by subjecting a random variable with a fixed distribution to some suitable transformations.[1] Different types of group families are as follows :

Location Family

This family is obtained by adding a constant to a random variable. Let <math>X</math> be a random variable and <math>a \in R</math> be a constant. Let <math display="inline">Y = X + a</math> . Then <math display="block">F_Y(y) = P(Y\leq y) = P(X+a \leq y) = P(X \leq y-a) = F_X(y-a) </math>For a fixed distribution , as <math>a </math> varies from <math>-\infty </math> to <math>\infty </math> , the distributions that we obtain constitute the location family.

Scale Family

This family is obtained by multiplying a random variable with a constant. Let <math>X</math> be a random variable and <math>c \in R^+</math> be a constant. Let <math display="inline">Y = cX</math> . Then<math display="block">F_Y(y) = P(Y\leq y) = P(cX \leq y) = P(X \leq y/c) = F_X(y/c) </math>

Location - Scale Family

This family is obtained by multiplying a random variable with a constant and then adding some other constant to it. Let <math>X </math> be a random variable , <math>a \in R</math> and <math>c \in R^+</math>be constants. Let <math>Y = cX + a </math>. Then

<math display="block">F_Y(y) = P(Y\leq y) = P(cX+a \leq y) = P(X \leq (y-a)/c) = F_X((y-a)/c) </math>

Note that it is important that <math display="inline">a \in R </math> and <math>c \in R^+ </math> in order to satisfy the properties mentioned in the following section.

Properties of the transformations

The transformation applied to the random variable must satisfy the following properties.[1]

  • Closure under composition
  • Closure under inversion

References

  1. 1,0 1,1 1,2 Шаблон:Cite book
  2. Cox, D.R. (2006) Principles of Statistical Inference, CUP. Шаблон:ISBN (Section 4.4.2)

Шаблон:Statistics-stub