statsmodels.stats.outliers_influence.OLSInfluence

class statsmodels.stats.outliers_influence.OLSInfluence(results)

class to calculate outlier and influence measures for OLS result

Parameters

resultsRegressionResults

currently assumes the results are from an OLS regression

Notes

One part of the results can be calculated without any auxiliary regression (some of which have the _internal postfix in the name. Other statistics require leave-one-observation-out (LOOO) auxiliary regression, and will be slower (mainly results with _external postfix in the name). The auxiliary LOOO regression only the required results are stored.

Using the LOO measures is currently only recommended if the data set is not too large. One possible approach for LOOO measures would be to identify possible problem observations with the _internal measures, and then run the leave-one-observation-out only with observations that are possible outliers. (However, this is not yet available in an automized way.)

This should be extended to general least squares.

The leave-one-variable-out (LOVO) auxiliary regression are currently not used.

Attributes

det_cov_params_not_obsi

determinant of cov_params of all LOOO regressions

params_not_obsi

parameter estimates for all LOOO regressions

Methods

cooks_distance()	Cooks distance
cov_ratio()	covariance ratio between LOOO and original
dfbeta()	dfbetas
dfbetas()	uses results from leave-one-observation-out loop
dffits()	dffits measure for influence of an observation
dffits_internal()	dffits measure for influence of an observation
ess_press()	Error sum of squares of PRESS residuals
get_resid_studentized_external([sigma])	calculate studentized residuals
hat_diag_factor()	Factor of diagonal of hat_matrix used in influence
hat_matrix_diag()	Diagonal of the hat_matrix for OLS
influence()	Influence measure
plot_index([y_var, threshold, title, ax, idx])	index plot for influence attributes
plot_influence([external, alpha, criterion, …])	Plot of influence in regression.
resid_press()	PRESS residuals
resid_std()	estimate of standard deviation of the residuals
resid_studentized()	Studentized residuals using variance from OLS
resid_studentized_external()	Studentized residuals using LOOO variance
resid_studentized_internal()	Studentized residuals using variance from OLS
resid_var()	estimate of variance of the residuals
sigma2_not_obsi()	error variance for all LOOO regressions
summary_frame()	Creates a DataFrame with all available influence results.
summary_table([float_fmt])	create a summary table with all influence and outlier measures