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  2. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    If the estimation is inadequate, we have to return to step one and attempt to build a better model. The data they used were from a gas furnace. These data are well known as the Box and Jenkins gas furnace data for benchmarking predictive models. Commandeur & Koopman (2007, §10.4) [2] argue that the Box–Jenkins approach is fundamentally ...

  3. Variance inflation factor - Wikipedia

    en.wikipedia.org/wiki/Variance_inflation_factor

    In statistics, the variance inflation factor (VIF) is the ratio of the variance of a parameter estimate when fitting a full model that includes other parameters to the variance of the parameter estimate if the model is fit with only the parameter on its own. [1]

  4. Identifiability analysis - Wikipedia

    en.wikipedia.org/wiki/Identifiability_analysis

    Estimation theory – Branch of statistics to estimate models based on measured data; Identifiability – Statistical property which a model must satisfy to allow precise inference; Parameter identification problem – Parameter estimation technique in statistics, particularly econometrics

  5. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    A given regression method will ultimately provide an estimate of , usually denoted ^ to distinguish the estimate from the true (unknown) parameter value that generated the data. Using this estimate, the researcher can then use the fitted value ^ = (, ^) for prediction or to assess the accuracy of the model in explaining the data.

  6. Estimation theory - Wikipedia

    en.wikipedia.org/wiki/Estimation_theory

    Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data.

  7. Method of moments (statistics) - Wikipedia

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

    In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.