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  2. Linear probability model - Wikipedia

    en.wikipedia.org/wiki/Linear_probability_model

    In statistics, a linear probability model (LPM) is a special case of a binary regression model. Here the dependent variable for each observation takes values which are either 0 or 1. The probability of observing a 0 or 1 in any one case is treated as depending on one or more explanatory variables .

  3. Taylor expansions for the moments of functions of random ...

    en.wikipedia.org/wiki/Taylor_expansions_for_the...

    In probability theory, it is possible to approximate the moments of a function f of a random variable X using Taylor expansions, provided that f is sufficiently differentiable and that the moments of X are finite. A simulation-based alternative to this approximation is the application of Monte Carlo simulations.

  4. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Birnbaum–Saunders distribution, also known as the fatigue life distribution, is a probability distribution used extensively in reliability applications to model failure times. The chi distribution. The noncentral chi distribution; The chi-squared distribution, which is the sum of the squares of n independent Gaussian random variables.

  5. Statistical model - Wikipedia

    en.wikipedia.org/wiki/Statistical_model

    Informally, a statistical model can be thought of as a statistical assumption (or set of statistical assumptions) with a certain property: that the assumption allows us to calculate the probability of any event. As an example, consider a pair of ordinary six-sided dice. We will study two different statistical assumptions about the dice.

  6. Category:Probabilistic models - Wikipedia

    en.wikipedia.org/wiki/Category:Probabilistic_models

    Pages in category "Probabilistic models" The following 32 pages are in this category, out of 32 total. ... Factored language model; Fast probability integration;

  7. Graphical model - Wikipedia

    en.wikipedia.org/wiki/Graphical_model

    A graphical model or probabilistic graphical model (PGM) or structured probabilistic model is a probabilistic model for which a graph expresses the conditional dependence structure between random variables. They are commonly used in probability theory, statistics—particularly Bayesian statistics—and machine learning.

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