class statsmodels.duration.hazard_regression.PHReg(endog, exog, status=None, entry=None, strata=None, offset=None, ties='breslow', missing='drop', **kwargs)
[source]
Fit the Cox proportional hazards regression model for right censored data.
Parameters: |
|
---|
Proportional hazards regression models should not include an explicit or implicit intercept. The effect of an intercept is not identified using the partial likelihood approach.
endog
, event
, strata
, entry
, and the first dimension of exog
all must have the same length
baseline_cumulative_hazard (params) | Estimate the baseline cumulative hazard and survival functions. |
baseline_cumulative_hazard_function (params) | Returns a function that calculates the baseline cumulative hazard function for each stratum. |
breslow_gradient (params) | Returns the gradient of the log partial likelihood, using the Breslow method to handle tied times. |
breslow_hessian (params) | Returns the Hessian of the log partial likelihood evaluated at params , using the Breslow method to handle tied times. |
breslow_loglike (params) | Returns the value of the log partial likelihood function evaluated at params , using the Breslow method to handle tied times. |
efron_gradient (params) | Returns the gradient of the log partial likelihood evaluated at params , using the Efron method to handle tied times. |
efron_hessian (params) | Returns the Hessian matrix of the partial log-likelihood evaluated at params , using the Efron method to handle tied times. |
efron_loglike (params) | Returns the value of the log partial likelihood function evaluated at params , using the Efron method to handle tied times. |
fit ([groups]) | Fit a proportional hazards regression model. |
fit_regularized ([method, alpha, …]) | Return a regularized fit to a linear regression model. |
from_formula (formula, data[, status, entry, …]) | Create a proportional hazards regression model from a formula and dataframe. |
get_distribution (params) | Returns a scipy distribution object corresponding to the distribution of uncensored endog (duration) values for each case. |
hessian (params) | Returns the Hessian matrix of the log partial likelihood function evaluated at params . |
information (params) | Fisher information matrix of model |
initialize () | Initialize (possibly re-initialize) a Model instance. |
loglike (params) | Returns the log partial likelihood function evaluated at params . |
predict (params[, exog, cov_params, endog, …]) | Returns predicted values from the proportional hazards regression model. |
robust_covariance (params) | Returns a covariance matrix for the proportional hazards model regresion coefficient estimates that is robust to certain forms of model misspecification. |
score (params) | Returns the score function evaluated at params . |
score_residuals (params) | Returns the score residuals calculated at a given vector of parameters. |
weighted_covariate_averages (params) | Returns the hazard-weighted average of covariate values for subjects who are at-risk at a particular time. |
endog_names | Names of endogenous variables |
exog_names | Names of exogenous variables |
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.duration.hazard_regression.PHReg.html