Family.predict()

statsmodels.genmod.families.family.Family.predict Family.predict(mu) [source] Linear predictors based on given mu values. Parameters: mu : array The mean response variables Returns: lin_pred : array Linear predictors based on the mean response variables. The value of the link function at the given mu.

Family.loglike()

statsmodels.genmod.families.family.Family.loglike Family.loglike(endog, mu, scale=1.0) [source] The loglikelihood function. Parameters: `endog` : array Usually the endogenous response variable. `mu` : array Usually but not always the fitted mean response variable. Returns: llf : float The value of the loglikelihood evaluated at (endog,mu). Notes : ?? : This is defined for each family. endog and mu are not restricted to : `endog` and `mu` respectively. For instance, the deviance func

Family.fitted()

statsmodels.genmod.families.family.Family.fitted Family.fitted(lin_pred) [source] Fitted values based on linear predictors lin_pred. Parameters: lin_pred : array Values of the linear predictor of the model. dot(X,beta) in a classical linear model. Returns: mu : array The mean response variables given by the inverse of the link function.

ExpTransf_gen.var()

statsmodels.sandbox.distributions.transformed.ExpTransf_gen.var ExpTransf_gen.var(*args, **kwds) Variance of the distribution Parameters: arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information) loc : array_like, optional location parameter (default=0) scale : array_like, optional scale parameter (default=1) Returns: var : float the variance of the distribution

Family.deviance()

statsmodels.genmod.families.family.Family.deviance Family.deviance(endog, mu, scale=1.0) [source] Deviance of (endog,mu) pair. Deviance is usually defined as twice the loglikelihood ratio. Parameters: endog : array-like The endogenous response variable mu : array-like The inverse of the link function at the linear predicted values. scale : float, optional An optional scale argument Returns: Deviance : array The value of deviance function defined below. Notes Deviance is defined

ExpTransf_gen.stats()

statsmodels.sandbox.distributions.transformed.ExpTransf_gen.stats ExpTransf_gen.stats(*args, **kwds) Some statistics of the given RV Parameters: arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information) loc : array_like, optional location parameter (default=0) scale : array_like, optional (discrete RVs only) scale parameter (default=1) moments : str, optional composed of letters [?mvsk?] defining which mo

ExpTransf_gen.std()

statsmodels.sandbox.distributions.transformed.ExpTransf_gen.std ExpTransf_gen.std(*args, **kwds) Standard deviation of the distribution. Parameters: arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information) loc : array_like, optional location parameter (default=0) scale : array_like, optional scale parameter (default=1) Returns: std : float standard deviation of the distribution

ExpTransf_gen.rvs()

statsmodels.sandbox.distributions.transformed.ExpTransf_gen.rvs ExpTransf_gen.rvs(*args, **kwds) Random variates of given type. Parameters: arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information). loc : array_like, optional Location parameter (default=0). scale : array_like, optional Scale parameter (default=1). size : int or tuple of ints, optional Defining number of random variates (default=1). Retu

ExpTransf_gen.ppf()

statsmodels.sandbox.distributions.transformed.ExpTransf_gen.ppf ExpTransf_gen.ppf(q, *args, **kwds) Percent point function (inverse of cdf) at q of the given RV. Parameters: q : array_like lower tail probability arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information) loc : array_like, optional location parameter (default=0) scale : array_like, optional scale parameter (default=1) Returns: x : array_l

ExpTransf_gen.sf()

statsmodels.sandbox.distributions.transformed.ExpTransf_gen.sf ExpTransf_gen.sf(x, *args, **kwds) Survival function (1-cdf) at x of the given RV. Parameters: x : array_like quantiles arg1, arg2, arg3,... : array_like The shape parameter(s) for the distribution (see docstring of the instance object for more information) loc : array_like, optional location parameter (default=0) scale : array_like, optional scale parameter (default=1) Returns: sf : array_like Survival function evalu