4.3.1.1.2. statsmodels.duration.hazard_regression.PHRegResults¶
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class
statsmodels.duration.hazard_regression.
PHRegResults
(model, params, cov_params, covariance_type='naive')[source]¶ Class to contain results of fitting a Cox proportional hazards survival model.
PHregResults inherits from statsmodels.LikelihoodModelResults
Parameters: See statsmodels.LikelihoodModelResults
Returns: Attributes
model : class instance
PHreg model instance that called fit.
normalized_cov_params : array
The sampling covariance matrix of the estimates
params : array
The coefficients of the fitted model. Each coefficient is the log hazard ratio corresponding to a 1 unit difference in a single covariate while holding the other covariates fixed.
bse : array
The standard errors of the fitted parameters.
See also
statsmodels.LikelihoodModelResults
4.3.1.1.2.1. Methods¶
__init__ (model, params, cov_params[, ...]) |
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baseline_cumulative_hazard () |
A list (corresponding to the strata) containing the baseline cumulative hazard function evaluated at the event points. |
baseline_cumulative_hazard_function () |
A list (corresponding to the strata) containing function objects that calculate the cumulative hazard function. |
bse () |
Returns the standard errors of the parameter estimates. |
conf_int ([alpha, cols, method]) |
Returns the confidence interval of the fitted parameters. |
cov_params ([r_matrix, column, scale, cov_p, ...]) |
Returns the variance/covariance matrix. |
f_test (r_matrix[, cov_p, scale, invcov]) |
Compute the F-test for a joint linear hypothesis. |
get_distribution () |
Returns a scipy distribution object corresponding to the distribution of uncensored endog (duration) values for each case. |
initialize (model, params, **kwd) |
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llf () |
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load (fname) |
load a pickle, (class method) |
martingale_residuals () |
The martingale residuals. |
normalized_cov_params () |
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predict ([endog, exog, strata, offset, pred_type]) |
Returns predicted values from the fitted proportional hazards regression model. |
pvalues () |
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remove_data () |
remove data arrays, all nobs arrays from result and model |
save (fname[, remove_data]) |
save a pickle of this instance |
schoenfeld_residuals () |
A matrix containing the Schoenfeld residuals. |
score_residuals () |
A matrix containing the score residuals. |
standard_errors () |
Returns the standard errors of the parameter estimates. |
summary ([yname, xname, title, alpha]) |
Summarize the proportional hazards regression results. |
t_test (r_matrix[, cov_p, scale, use_t]) |
Compute a t-test for a each linear hypothesis of the form Rb = q |
tvalues () |
Return the t-statistic for a given parameter estimate. |
wald_test (r_matrix[, cov_p, scale, invcov, ...]) |
Compute a Wald-test for a joint linear hypothesis. |
weighted_covariate_averages () |
The average covariate values within the at-risk set at each event time point, weighted by hazard. |