/Statsmodels

# statsmodels.multivariate.multivariate_ols._MultivariateOLSResults.mv_test

`_MultivariateOLSResults.mv_test(hypotheses=None)` [source]

Linear hypotheses testing

Parameters: hypotheses (A list of tuples) – Hypothesis `L*B*M = C` to be tested where B is the parameters in regression Y = X*B. Each element is a tuple of length 2, 3, or 4: (name, contrast_L) (name, contrast_L, transform_M) (name, contrast_L, transform_M, constant_C) containing a string `name`, the contrast matrix L, the transform matrix M (for transforming dependent variables), and right-hand side constant matrix constant_C, respectively. `contrast_L : 2D array or an array of strings` Left-hand side contrast matrix for hypotheses testing. If 2D array, each row is an hypotheses and each column is an independent variable. At least 1 row (1 by k_exog, the number of independent variables) is required. If an array of strings, it will be passed to patsy.DesignInfo().linear_constraint. `transform_M : 2D array or an array of strings or None, optional` Left hand side transform matrix. If `None` or left out, it is set to a k_endog by k_endog identity matrix (i.e. do not transform y matrix). If an array of strings, it will be passed to patsy.DesignInfo().linear_constraint. `constant_C : 2D array or None, optional` Right-hand side constant matrix. if `None` or left out it is set to a matrix of zeros Must has the same number of rows as contrast_L and the same number of columns as transform_M If `hypotheses` is None: 1) the effect of each independent variable on the dependent variables will be tested. Or 2) if model is created using a formula, `hypotheses` will be created according to `design_info`. 1) and 2) is equivalent if no additional variables are created by the formula (e.g. dummy variables for categorical variables and interaction terms) results _MultivariateOLSResults

#### Notes

Tests hypotheses of the form

L * params * M = C

where `params` is the regression coefficient matrix for the linear model y = x * params, `L` is the contrast matrix, `M` is the dependent variable transform matrix and C is the constant matrix.