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  2. White test - Wikipedia

    en.wikipedia.org/wiki/White_test

    White test is a statistical test that establishes whether the variance of the errors in a regression model is constant: that is for homoskedasticity. This test, and an estimator for heteroscedasticity-consistent standard errors , were proposed by Halbert White in 1980. [ 1 ]

  3. All models are wrong - Wikipedia

    en.wikipedia.org/wiki/All_models_are_wrong

    George Box. The phrase "all models are wrong" was first attributed to George Box in a 1976 paper published in the Journal of the American Statistical Association.In the paper, Box uses the phrase to refer to the limitations of models, arguing that while no model is ever completely accurate, simpler models can still provide valuable insights if applied judiciously. [2]

  4. Identifiability - Wikipedia

    en.wikipedia.org/wiki/Identifiability

    Identifiability of the model in the sense of invertibility of the map is equivalent to being able to learn the model's true parameter if the model can be observed indefinitely long. Indeed, if {X t} ⊆ S is the sequence of observations from the model, then by the strong law of large numbers,

  5. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    Instead, they must control for variables using statistics. Observational studies are used when controlled experiments may be unethical or impractical. For instance, if a researcher wished to study the effect of unemployment ( the independent variable ) on health ( the dependent variable ), it would be considered unethical by institutional ...

  6. Restricted maximum likelihood - Wikipedia

    en.wikipedia.org/wiki/Restricted_maximum_likelihood

    In statistics, the restricted (or residual, or reduced) maximum likelihood (REML) approach is a particular form of maximum likelihood estimation that does not base estimates on a maximum likelihood fit of all the information, but instead uses a likelihood function calculated from a transformed set of data, so that nuisance parameters have no effect.

  7. Robust regression - Wikipedia

    en.wikipedia.org/wiki/Robust_regression

    The simplest methods of estimating parameters in a regression model that are less sensitive to outliers than the least squares estimates, is to use least absolute deviations. Even then, gross outliers can still have a considerable impact on the model, motivating research into even more robust approaches.

  8. Net reclassification improvement - Wikipedia

    en.wikipedia.org/wiki/Net_reclassification...

    Net reclassification improvement (NRI) is an index that attempts to quantify how well a new model reclassifies subjects - either appropriately or inappropriately - as compared to an old model. [1] While c-statistics or AUC has been the standard metric for quantifying improvements over the last few decades, several studies have analyzed the ...

  9. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    Since the null hypothesis for Tukey's test states that all means being compared are from the same population (i.e. μ 1 = μ 2 = μ 3 = ... = μ k), the means should be normally distributed (according to the central limit theorem) with the same model standard deviation σ, estimated by the merged standard error, , for all the samples; its ...