Algorithmic Inference
In algorithmic inference, the property of a statistic that is of most relevance is the pivoting step which allows to transference of probability-considerations from the sample distribution to the distribution of the parameters representing the population distribution in such a way that the conclusion of this statistical inference step is compatible with the sample actually observed.
By default, capital letters (such as U, X) will denote random variables and small letters (u, x) their corresponding realizations and with gothic letters (such as ) the domain where the variable takes specifications. Facing a sample, given a sampling mechanism, with scalar, for the random variable X, we have
The sampling mechanism, of the statistic s, as a function ? of with specifications in, has an explaining function defined by the master equation:
for suitable seeds and parameter ?
Read more about this topic: Well-behaved Statistic
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