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  2. Principal component regression - Wikipedia

    en.wikipedia.org/wiki/Principal_component_regression

    In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). PCR is a form of reduced rank regression . [ 1 ] More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model .

  3. Mean squared prediction error - Wikipedia

    en.wikipedia.org/wiki/Mean_squared_prediction_error

    First, with a data sample of length n, the data analyst may run the regression over only q of the data points (with q < n), holding back the other n – q data points with the specific purpose of using them to compute the estimated model’s MSPE out of sample (i.e., not using data that were used in the model estimation process).

  4. MedCalc - Wikipedia

    en.wikipedia.org/wiki/MedCalc

    Survival analysis includes Cox regression (Proportional hazards model) and Kaplan–Meier survival analysis. Procedures for method evaluation and method comparison include ROC curve analysis, [6] Bland–Altman plot, [7] as well as Deming and Passing–Bablok regression. [8]

  5. Breusch–Godfrey test - Wikipedia

    en.wikipedia.org/wiki/Breusch–Godfrey_test

    The Breusch–Godfrey test is a test for autocorrelation in the errors in a regression model. It makes use of the residuals from the model being considered in a regression analysis, and a test statistic is derived from these. The null hypothesis is that there is no serial correlation of any order up to p. [3]

  6. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    First, regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning. Second, in some situations regression analysis can be used to infer causal relationships between the independent and dependent variables. Importantly, regressions by themselves only reveal ...

  7. Outline of regression analysis - Wikipedia

    en.wikipedia.org/wiki/Outline_of_regression_analysis

    The following outline is provided as an overview of and topical guide to regression analysis: Regression analysis – use of statistical techniques for learning about the relationship between one or more dependent variables (Y) and one or more independent variables (X).

  8. Mallows's Cp - Wikipedia

    en.wikipedia.org/wiki/Mallows's_Cp

    In statistics, Mallows's, [1] [2] named for Colin Lingwood Mallows, is used to assess the fit of a regression model that has been estimated using ordinary least squares.It is applied in the context of model selection, where a number of predictor variables are available for predicting some outcome, and the goal is to find the best model involving a subset of these predictors.

  9. Polynomial regression - Wikipedia

    en.wikipedia.org/wiki/Polynomial_regression

    Although polynomial regression is technically a special case of multiple linear regression, the interpretation of a fitted polynomial regression model requires a somewhat different perspective. It is often difficult to interpret the individual coefficients in a polynomial regression fit, since the underlying monomials can be highly correlated.

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