# statsmodels.stats.multitest.RegressionFDR¶

class statsmodels.stats.multitest.RegressionFDR(endog, exog, regeffects, method='knockoff', **kwargs)[source]

Control FDR in a regression procedure.

Parameters: endog (array-like) – The dependent variable of the regression exog (array-like) – The independent variables of the regression regeffects (RegressionEffects instance) – An instance of a RegressionEffects class that can compute effect sizes for the regression coefficients. method (string) – The approach used to asssess and control FDR, currently must be ‘knockoff’. Returns an instance of the RegressionFDR class. The fdr attribute holds the estimated false discovery rates.

Notes

This class Implements the knockoff method of Barber and Candes. This is an approach for controlling the FDR of a variety of regression estimation procedures, including correlation coefficients, OLS regression, OLS with forward selection, and LASSO regression.

For other approaches to FDR control in regression, see the statsmodels.stats.multitest module. Methods provided in that module use Z-scores or p-values, and therefore require standard errors for the coefficient estimates to be available.

The default method for constructing the augmented design matrix is the ‘equivariant’ approach, set design_method=’sdp’ to use an alternative approach involving semidefinite programming. See Barber and Candes for more information about both approaches. The sdp approach requires that the cvxopt package be installed.

Methods

 summary() threshold(tfdr) Returns the threshold statistic for a given target FDR.