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・ Statistical inference
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Statistical model
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Statistical model : ウィキペディア英語版
Statistical model
A statistical model embodies a set of assumptions concerning the generation of the observed data, and similar data from a larger population. A model represents, often in considerably idealized form, the data-generating process. The model assumptions describe a set of probability distributions, some of which are assumed to adequately approximate the distribution from which a particular data set is sampled.
A model is usually specified by mathematical equations that relate one or more random variables and possibly other non-random variables. As such, "a model is a formal representation of a theory" (Herman Adèr quoting Kenneth Bollen).
All statistical hypothesis tests and all statistical estimators are derived from statistical models. More generally, statistical models are part of the foundation of statistical inference.
==Formal definition==
In mathematical terms, a statistical model is usually thought of as a pair (S, \mathcal), where S is the set of possible observations, i.e. the sample space, and \mathcal is a set of probability distributions on S.
The intuition behind this definition is as follows. It is assumed that there is a "true" probability distribution that generates the observed data. We choose \mathcal to represent a set (of distributions) which contains a distribution that adequately approximates the true distribution. Note that we do not require that \mathcal contains the true distribution, and in practice that is rarely the case. Indeed, as Burnham & Anderson state, "A model is a simplification or approximation of reality and hence will not reflect all of reality"—whence the saying "all models are wrong".
The set \mathcal is almost always parameterized: \mathcal=\. The set \Theta defines the ''parameters'' of the model. A parameterization is generally required to have distinct parameter values give rise to distinct distributions, i.e. to meet this condition: P_ = P_ \Rightarrow \theta_1 = \theta_2. A parameterization that meets the condition is said to be ''identifiable''.〔

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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