Use the properties of a LinearModel object to investigate a fitted linear regression model. The object properties include information about coefficient estimates, summary statistics, fitting method, and …

This example shows how to perform simple linear regression using the accidents dataset. The example also shows you how to calculate the coefficient of determination R2 to evaluate the regressions. The …

Linear Regression Prepare Data To begin fitting a regression, put your data into a form that fitting functions expect. All regression techniques begin with input data in an array X and response data in …

Import and prepare data, fit a linear regression model, test and improve its quality, and share the model.

A linear regression model describes the relationship between a response (output) variable and a predictor (input) variable. In a linear regression model, the response variable is expressed as an …

Linear regression is a statistical modeling technique used to describe a continuous response variable as a function of one or more predictor variables. It can help you understand and predict the behavior of …

In a multiple linear regression model, the response variable depends on more than one predictor variable. You can perform multiple linear regression with or without the LinearModel object, or by …

Choose a Regression Function Regression is the process of fitting models to data. The models must have numerical responses. For models with categorical responses, see Parametric Classification or …

Multivariate Linear Regression Introduction to Multivariate Methods Large, high-dimensional data sets are common in the modern era of computer-based instrumentation and electronic data storage. High …

Parametric nonlinear models represent the relationship between a continuous response variable and one or more continuous predictor variables.