statsmodels.stats.multitest.RegressionFDR#
- class statsmodels.stats.multitest.RegressionFDR(endog, exog, regeffects, method='knockoff', rng=None, **kwargs)[source]#
Control FDR in a regression procedure
- Parameters:
- endogarray_like
The dependent variable of the regression
- exogarray_like
The independent variables of the regression
- regeffects
RegressionEffectsinstance An instance of a RegressionEffects class that can compute effect sizes for the regression coefficients.
- method
str The approach used to assess and control FDR, currently must be ‘knockoff’.
- rng{
None,int, array_like[int],numpy.random.Generator,numpy.random.RandomState},optional If rng is None, a new
Generatoris created using fresh entropy from the operating system. If rng is an int or array of ints, a newGeneratoris created, seeded with rng. If rng is already aGeneratororRandomStateinstance, that instance is used.- **kwargs
Additional keyword arguments. Currently supports design_method, the approach used to construct the augmented design matrix, either ‘equi’ (the default) or ‘sdp’.
Methods
threshold(tfdr)Return the threshold statistic for a given target FDR
summary
- Returns:
ReturnsaninstanceoftheRegressionFDRclass.Thefdrattributeholdstheestimatedfalsediscoveryrates.
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