3.4.6.3.3.1.22. statsmodels.emplike.originregress.OriginResults.el_test¶

OriginResults.el_test(b0_vals, param_nums, method='nm', stochastic_exog=1, return_weights=0)[source]¶

Returns the llr and p-value for a hypothesized parameter value for a regression that goes through the origin

Parameters:

b0_vals : 1darray

The hypothesized value to be tested

param_num : 1darray

Which parameters to test. Note this uses python indexing but the ‘0’ parameter refers to the intercept term, which is assumed 0. Therefore, param_num should be > 0.

return_weights : bool

If true, returns the weights that optimize the likelihood ratio at b0_vals. Default is False

method : string

Can either be ‘nm’ for Nelder-Mead or ‘powell’ for Powell. The optimization method that optimizes over nuisance parameters. Default is ‘nm’

stochastic_exog : bool

When TRUE, the exogenous variables are assumed to be stochastic. When the regressors are nonstochastic, moment conditions are placed on the exogenous variables. Confidence intervals for stochastic regressors are at least as large as non-stochastic regressors. Default is TRUE

Returns:

res : tuple

pvalue and likelihood ratio