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In computer programming, a parameter or a formal argument is a special kind of variable used in a subroutine to refer to one of the pieces of data provided as input to the subroutine.
Suppose that we have an indexed family of distributions. If the index is also a parameter of the members of the family, then the family is a parameterized family.Among parameterized families of distributions are the normal distributions, the Poisson distributions, the binomial distributions, and the exponential family of distributions.
In probability theory and statistics, a shape parameter (also known as form parameter) [1] is a kind of numerical parameter of a parametric family of probability distributions [2] that is neither a location parameter nor a scale parameter (nor a function of these, such as a rate parameter).
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.
The W hierarchy is a collection of computational complexity classes. A parameterized problem is in the class W[i], if every instance (,) can be transformed (in fpt-time) to a combinatorial circuit that has weft at most i, such that (,) if and only if there is a satisfying assignment to the inputs that assigns 1 to exactly k inputs.
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An illustration of the Overton window, along with Treviño's degrees of acceptance. The Overton window is the range of subjects and arguments politically acceptable to the mainstream population at a given time. [1]
The general treatment of nuisance parameters can be broadly similar between frequentist and Bayesian approaches to theoretical statistics. It relies on an attempt to partition the likelihood function into components representing information about the parameters of interest and information about the other (nuisance) parameters.