TD_MULTIVAR_REGR is a multivariate linear regression function. Using a formula that defines the relationship between multiple independent variables and a single dependent variable. The goal of multivariate regression is to create a model that predicts the value of the dependent variable based on the values of the independent variables.
For example, a study is conducted to see how House_Prices (response variable) is affected by Salary, Square_footage, Number of Bedrooms, and Size of Lot (the explanatory variables). The TD_MULTIVAR_REGR function performs a fitting operation to fit the data to a multidimensional surface.
The function calculates the coefficients of the independent variables and the intercept of the regression equation, which are used to predict the value of the dependent variable for new observations.
The function takes as input a dataset containing the variables to be analyzed, along with parameters specifying the variables to be used in the analysis and the method for calculating the regression coefficients. The output of the function includes the coefficients, and other statistical measures of the model's fit.