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  2. Semiparametric model - Wikipedia

    en.wikipedia.org/wiki/Semiparametric_model

    A statistical model is a parameterized family of distributions: {:} indexed by a parameter. A parametric model is a model in which the indexing parameter θ {\displaystyle \theta } is a vector in k {\displaystyle k} -dimensional Euclidean space , for some nonnegative integer k {\displaystyle k} . [ 1 ]

  3. Nonparametric statistics - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_statistics

    Nonparametric statistics is a type of statistical analysis that makes minimal assumptions about the underlying distribution of the data being studied. Often these models are infinite-dimensional, rather than finite dimensional, as in parametric statistics. [1]

  4. Semiparametric regression - Wikipedia

    en.wikipedia.org/wiki/Semiparametric_regression

    In statistics, semiparametric regression includes regression models that combine parametric and nonparametric models. They are often used in situations where the fully nonparametric model may not perform well or when the researcher wants to use a parametric model but the functional form with respect to a subset of the regressors or the density of the errors is not known.

  5. Truncation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Truncation_(statistics)

    Regression models with such dependent variables require special care that properly recognizes the truncated nature of the variable. Estimation of such truncated regression model can be done in parametric, [5] [6] [7] or semi- and non-parametric frameworks. [8] [9]

  6. Nonparametric regression - Wikipedia

    en.wikipedia.org/wiki/Nonparametric_regression

    Nonparametric regression is a category of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. That is, no parametric equation is assumed for the relationship between predictors and dependent variable.

  7. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    A third class, semi-parametric models, includes features of both. Parametric models make "specific assumptions with regard to one or more of the population parameters that characterize the underlying distribution(s)". [3] Non-parametric models "typically involve fewer assumptions of structure and distributional form [than parametric models] but ...

  8. Category:Nonparametric statistics - Wikipedia

    en.wikipedia.org/wiki/Category:Nonparametric...

    Nonparametric statistics is a branch of statistics concerned with non-parametric statistical models and non-parametric statistical tests. Non-parametric statistics are statistics that do not estimate population parameters. In contrast, see parametric statistics. Nonparametric models differ from parametric models in that the model structure is ...

  9. Econometric model - Wikipedia

    en.wikipedia.org/wiki/Econometric_model

    An econometric model then is a set of joint probability distributions to which the true joint probability distribution of the variables under study is supposed to belong. In the case in which the elements of this set can be indexed by a finite number of real-valued parameters , the model is called a parametric model ; otherwise it is a ...