ó áp7]c@sAdZddlZddlmZd„Zdddd„ZdS(sZAdditional functions prediction standard errors and confidence intervals A: josef pktd iÿÿÿÿN(tstatscCsztj|ƒ}|jdkr7|dd…df}n?|jdkrXtj|ƒ}n|jdkrvtdƒ‚n|S(sM convert array_like to 2d from 1d or 0d not tested because not used iNistoo many dimensions(tnptasarraytndimtNonet atleast_2dt ValueError(tx((sElib/python2.7/site-packages/statsmodels/sandbox/regression/predstd.pyt atleast_2dcol sgš™™™™™©?c Csz|jƒ}|dkrK|jj}|j}|dkrö|jj}qön«tj|ƒ}|jd|jdkrƒt dƒ‚n|jj |j |ƒ}|dkr°d}nFtj |ƒ}|j dkröt|ƒ|jdkröt dƒ‚n|j||tj||jƒjjdƒ}tj|ƒ}tjj|d|jƒ}|||} |||} || | fS(scalculate standard deviation and confidence interval for prediction applies to WLS and OLS, not to general GLS, that is independently but not identically distributed observations Parameters ---------- res : regression result instance results of WLS or OLS regression required attributes see notes exog : array_like (optional) exogenous variables for points to predict weights : scalar or array_like (optional) weights as defined for WLS (inverse of variance of observation) alpha : float (default: alpha = 0.05) confidence level for two-sided hypothesis Returns ------- predstd : array_like, 1d standard error of prediction same length as rows of exog interval_l, interval_u : array_like lower und upper confidence bounds Notes ----- The result instance needs to have at least the following res.model.predict() : predicted values or res.fittedvalues : values used in estimation res.cov_params() : covariance matrix of parameter estimates If exog is 1d, then it is interpreted as one observation, i.e. a row vector. testing status: not compared with other packages References ---------- Greene p.111 for OLS, extended to WLS by analogy iswrong shape of exoggð?is+weights and exog do not have matching shapeg@N(t cov_paramsRtmodeltexogt fittedvaluestweightsRRtshapeRtpredicttparamsRtsizetlent mse_residtdottTtsumtsqrtRtttisftdf_resid( tresR R talphatcovbt predictedtpredvartpredstdttppft interval_ut interval_l((sElib/python2.7/site-packages/statsmodels/sandbox/regression/predstd.pytwls_prediction_stds*/       (0(t__doc__tnumpyRtscipyRRRR$(((sElib/python2.7/site-packages/statsmodels/sandbox/regression/predstd.pyts