B Z1&@s@dZddlZddlmZGdddeZd ddZd d d ZdS) zM Created on Fri Dec 19 11:29:18 2014 Author: Josef Perktold License: BSD-3 N)statsc@sXeZdZdddZeddZeddZedd Zdd d ZdddZ dddZ dS)PredictionResultsNc Csv||_||_||_||_||_||_||_|dks:|dkrJtj|_ d|_ n(|dkrftj |_ |jf|_ n ||_ d|_ dS)Nnormt) predicted_mean var_pred_meandf var_resid row_labelslinpredlinkrrdist dist_argsr) selfrrr r rr r r rr=lib/python3.7/site-packages/statsmodels/genmod/_prediction.py__init__s zPredictionResults.__init__cCstt|j|jS)N)NotImplementedErrornpsqrtrr )rrrrse_obs%szPredictionResults.se_obscCs t|jS)N)rrr)rrrrse_mean*szPredictionResults.se_meancCs |j|jS)N)rr)rrrrtvalues.szPredictionResults.tvaluesr two-sidedcCs|j||j}|dkr8|jjt|f|jd}nD|dkrV|jj|f|j}n&|dkrt|jj|f|j}ntd||fS)a3z- or t-test for hypothesis that mean is equal to value Parameters ---------- value : array_like value under the null hypothesis alternative : string 'two-sided', 'larger', 'smaller' Returns ------- stat : ndarray test statistic pvalue : ndarray p-value of the hypothesis test, the distribution is given by the attribute of the instance, specified in `__init__`. Default if not specified is the normal distribution. )z two-sidedz2-sidedZ2s)Zlargerl)Zsmallerszinvalid alternative) rrrZsfrabsrZcdf ValueError)rvalueZ alternativestatZpvaluerrrt_test3s zPredictionResults.t_testendpoint皙?c Kstddd}|j||k}|dkrL|sL|jj|dd}|j|}nX|dksX|r|j}|jj d|df|j } |j | |} |j | |} t | | f}|S) a Returns the confidence interval of the value, `effect` of the constraint. This is currently only available for t and z tests. Parameters ---------- alpha : float, optional The significance level for the confidence interval. ie., The default `alpha` = .05 returns a 95% confidence interval. kwds : extra keyword arguments currently ignored, only for compatibility, consistent signature Returns ------- ci : ndarray, (k_constraints, 2) The array has the lower and the upper limit of the confidence interval in the columns. rr"F)alphaZobsZdeltag@) rZlinspacer inverseallr conf_intrrZppfrrZ column_stack) rmethodr&kwdsZtmpZ is_linearZ ci_linearZciZseqlowerupperrrrr)Ws  zPredictionResults.conf_intr(cCsddl}ddlm}|j|d}|}|j|d<|j|d<|dddf|d<|dddf|d<||_|j||j| d }|S) Nr) OrderedDict)r&ZmeanZmean_seZ mean_ci_lowerr$Z mean_ci_upper)indexcolumns) ZpandasZstatsmodels.compat.collectionsr/r)rrtableZ DataFramer keys)rZwhatr&Zpdr/Zci_meanZ to_includeresrrr summary_frame~s      zPredictionResults.summary_frame)NNNNNN)rr)r"r#)r(r#) __name__ __module__ __qualname__rpropertyrrrr!r)r5rrrrrs     $ 'rTc Cs|r6t|jdr6|dk r6ddlm}||jjjj|}|dk r|dkr^t|dd}t|r^d}t |}|j dkr|jj j dks|jj j ddkr|dddf}t |}n6|jj }|dkrt|jdd}|dkrt|jjdd}|dk r.t |}|jdkr.|j dks&|j d|j dkr.td d |d <|jj|j|f|} |} |jjj|j} | d |t | |jjd} |j} |jd kr|jd} |dk r| |} ddg|j}t| | | |j ||||dS)a^ compute prediction results Parameters ---------- exog : array-like, optional The values for which you want to predict. transform : bool, optional If the model was fit via a formula, do you want to pass exog through the formula. Default is True. E.g., if you fit a model y ~ log(x1) + log(x2), and transform is True, then you can pass a data structure that contains x1 and x2 in their original form. Otherwise, you'd need to log the data first. weights : array_like, optional Weights interpreted as in WLS, used for the variance of the predicted residual. args, kwargs : Some models can take additional arguments or keywords, see the predict method of the model for the details. Returns ------- prediction_results : generalized_linear_model.PredictionResults The prediction results instance contains prediction and prediction variance and can on demand calculate confidence intervals and summary tables for the prediction of the mean and of new observations. ZformulaNr)dmatrixr0r$weightsr zweights has wrong shapeFZlinearrz fixed scalescalerr)r rr r r )!hasattrZmodelZpatsyr:dataZ design_infoZbuildergetattrcallablerasarrayndimexogshapeZ atleast_2dsizerZpredictparams cov_paramsZfamilyr inverse_derivrdotTsumr<Zcov_typeZcov_kwdsZuse_trZdf_resid)rrC transformr;r r r Z pred_kwdsr:rZcovb link_derivrr rrrrget_prediction_glmsL!        ""   rNc Csddlm}|dkr$|dkr$|}|dkrs  X