Generalized linear model and Multivariate adaptive regression splines

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Generalized linear model and Multivariate adaptive regression splines

Generalized linear model vs. Multivariate adaptive regression splines

In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary linear regression that allows for response variables that have error distribution models other than a normal distribution. In statistics, multivariate adaptive regression splines (MARS) is a form of regression analysis introduced by Jerome H. Friedman in 1991.

Similarities between Generalized linear model and Multivariate adaptive regression splines

Generalized linear model and Multivariate adaptive regression splines have 5 things in common (in Unionpedia): Dependent and independent variables, Generalized additive model, Linear regression, Logistic regression, Statistics.

Dependent and independent variables

In mathematical modeling, statistical modeling and experimental sciences, the values of dependent variables depend on the values of independent variables.

Dependent and independent variables and Generalized linear model · Dependent and independent variables and Multivariate adaptive regression splines · See more »

Generalized additive model

In statistics, a generalized additive model (GAM) is a generalized linear model in which the linear predictor depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions.

Generalized additive model and Generalized linear model · Generalized additive model and Multivariate adaptive regression splines · See more »

Linear regression

In statistics, linear regression is a linear approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables).

Generalized linear model and Linear regression · Linear regression and Multivariate adaptive regression splines · See more »

Logistic regression

In statistics, the logistic model (or logit model) is a statistical model that is usually taken to apply to a binary dependent variable.

Generalized linear model and Logistic regression · Logistic regression and Multivariate adaptive regression splines · See more »

Statistics

Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

Generalized linear model and Statistics · Multivariate adaptive regression splines and Statistics · See more »

The list above answers the following questions

What Generalized linear model and Multivariate adaptive regression splines have in common
What are the similarities between Generalized linear model and Multivariate adaptive regression splines

Generalized linear model and Multivariate adaptive regression splines Comparison

Generalized linear model has 90 relations, while Multivariate adaptive regression splines has 41. As they have in common 5, the Jaccard index is 3.82% = 5 / (90 + 41).

References

This article shows the relationship between Generalized linear model and Multivariate adaptive regression splines. To access each article from which the information was extracted, please visit:

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