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  2. Robust regression - Wikipedia

    en.wikipedia.org/wiki/Robust_regression

    A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations). Robust ...

  3. Nonparametric regression - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_regression

    Kernel regression estimates the continuous dependent variable from a limited set of data points by convolving the data points' locations with a kernel function—approximately speaking, the kernel function specifies how to "blur" the influence of the data points so that their values can be used to predict the value for nearby locations.

  4. Nonlinear regression - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_regression

    The independent or explanatory variable (say X) can be split up into classes or segments and linear regression can be performed per segment. Segmented regression with confidence analysis may yield the result that the dependent or response variable (say Y) behaves differently in the various segments. [3]

  5. Bayesian multivariate linear regression - Wikipedia

    en.wikipedia.org/wiki/Bayesian_multivariate...

    In statistics, Bayesian multivariate linear regression is a Bayesian approach to multivariate linear regression, i.e. linear regression where the predicted outcome is a vector of correlated random variables rather than a single scalar random variable.

  6. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/wiki/Multinomial_logistic...

    The value of the actual variable is then determined in a non-random fashion from these latent variables (i.e. the randomness has been moved from the observed outcomes into the latent variables), where outcome k is chosen if and only if the associated utility (the value of ,) is greater than the utilities of all the other choices, i.e. if the ...

  7. Multivariate probit model - Wikipedia

    en.wikipedia.org/wiki/Multivariate_probit_model

    In statistics and econometrics, the multivariate probit model is a generalization of the probit model used to estimate several correlated binary outcomes jointly. For example, if it is believed that the decisions of sending at least one child to public school and that of voting in favor of a school budget are correlated (both decisions are binary), then the multivariate probit model would be ...

  8. Hidden Uses for Common Household Products Most People Don't ...

    www.aol.com/finance/hidden-uses-common-household...

    1. Tennis Ball. Tennis balls are so useful that you may want to buy some to keep around the house even if you don’t play. For example, half a tennis ball can help screw open tight caps.

  9. Vector autoregression - Wikipedia

    en.wikipedia.org/wiki/Vector_autoregression

    A VAR model describes the evolution of a set of k variables, called endogenous variables, over time. Each period of time is numbered, t = 1, ..., T. The variables are collected in a vector, y t, which is of length k. (Equivalently, this vector might be described as a (k × 1)-matrix.) The vector is modelled as a linear function of its previous ...