enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Ordered logit - Wikipedia

    en.wikipedia.org/wiki/Ordered_logit

    In statistics, the ordered logit model or proportional odds logistic regression is an ordinal regression model—that is, a regression model for ordinal dependent variables—first considered by Peter McCullagh. [1]

  3. Multinomial logistic regression - Wikipedia

    en.wikipedia.org/.../Multinomial_logistic_regression

    Multinomial logistic regression is known by a variety of other names, including polytomous LR, [2] [3] multiclass LR, softmax regression, multinomial logit (mlogit), the maximum entropy (MaxEnt) classifier, and the conditional maximum entropy model. [4]

  4. Ordinal regression - Wikipedia

    en.wikipedia.org/wiki/Ordinal_regression

    Another approach is given by Rennie and Srebro, who, realizing that "even just evaluating the likelihood of a predictor is not straight-forward" in the ordered logit and ordered probit models, propose fitting ordinal regression models by adapting common loss functions from classification (such as the hinge loss and log loss) to the ordinal case ...

  5. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    In statistics, the logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis , logistic regression [ 1 ] (or logit regression ) estimates the parameters of a logistic model (the coefficients in the linear or non linear ...

  6. Discrete choice - Wikipedia

    en.wikipedia.org/wiki/Discrete_choice

    The "mixed exploded logit" model is obtained by probability of the ranking, given above, for L ni in the mixed logit model (model I). This model is also known in econometrics as the rank ordered logit model and it was introduced in that field by Beggs, Cardell and Hausman in 1981.

  7. Choice modelling - Wikipedia

    en.wikipedia.org/wiki/Choice_modelling

    These often begin with the conditional logit model - traditionally, although slightly misleadingly, referred to as the multinomial logistic (MNL) regression model by choice modellers. The MNL model converts the observed choice frequencies (being estimated probabilities, on a ratio scale) into utility estimates (on an interval scale) via the ...

  8. Multinomial probit - Wikipedia

    en.wikipedia.org/wiki/Multinomial_probit

    The multinomial probit model is a statistical model that can be used to predict the likely outcome of an unobserved multi-way trial given the associated explanatory variables. In the process, the model attempts to explain the relative effect of differing explanatory variables on the different outcomes.

  9. General linear model - Wikipedia

    en.wikipedia.org/wiki/General_linear_model

    The general linear model incorporates a number of different statistical models: ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary linear regression, t-test and F-test. The general linear model is a generalization of multiple linear regression to the case of more than one dependent variable.