ó âp7]c@ sådZddlmZddlZddljZddljZ ddl m Z ddl m Z ddlmZddljjZddljjjZddljjjZejZdefd„ƒYZd efd „ƒYZdS( s Impulse reponse-related code iÿÿÿÿ(tdivisionN(tcache_readonly(t chain_dot(trangetBaseIRAnalysisc B s˜eZdZd dd eed„Zeed„Zd„Zd„Zed d dd d e ddd d d „ Z ed d dd d e ddd d „ Z RS( sƒ Base class for plotting and computing IRF-related statistics, want to be able to handle known and estimated processes i cC s¤||_||_|j|j|j|_|_|_||_|dkrh|j }t j |ƒ}n||_ ||_ |j|ƒ|_|r­|j|d|ƒ|_n|j|d|ƒ|_|jjddƒ|_|rþ|jjddƒ|_n|jjddƒ|_|sm|jƒ|_|rOtj|jƒ|ƒ|_qmtj|jƒ|ƒ|_n|r‹tj|j ƒ|_!ntj|j"ƒ|_!dS(NtPtaxisi(#tmodeltperiodstneqstk_artnobstlagstTtordertNonetsigma_utlatcholeskyRtsvartma_reptirfst svar_ma_rept svar_irfst orth_ma_rept orth_irfstcumsumt cum_effectstsvar_cum_effectstorth_cum_effectstlong_run_effectst lr_effectstnptdottsvar_lr_effectstorth_lr_effectstutilt comp_matrixtvar_rept_Atcoefs(tselfRRRRRtvecmtsigma((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pyt__init__s2  &     cC s%|r |jS|r|jS|jSdS(N(RRR(R)torthR((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pyt _choose_irfsQs cO s t‚dS(N(tNotImplementedError(R)targstkwargs((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pytcovYscO s t‚dS(N(R/(R)R0R1((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pytcum_effect_cov\sgš™™™™™©?tasymièc C só|j} |j} |j}|r6|r6tdƒ‚n|j||ƒ}|rWd}n|rfd}nd}|tkrd}n2|dkrœtd ƒ‚n|dkr½|jd |ƒ}n|dkrö|jd |d |d | d|d| ƒ}n|dkr5|j d |d |d | d|d| d| ƒ}n|dkrt|j d |d |d | d|d| d| ƒ}n|d kr³|j d |d |d | d|d| d| ƒ}nt j |||||jj|d|d|d|d|ƒ}|S(se Plot impulse responses Parameters ---------- orth : bool, default False Compute orthogonalized impulse responses impulse : string or int variable providing the impulse response : string or int variable affected by the impulse signif : float (0 < signif < 1) Significance level for error bars, defaults to 95% CI subplot_params : dict To pass to subplot plotting funcions. Example: if fonts are too big, pass {'fontsize' : 8} or some number to your taste. plot_params : dict plot_stderr: bool, default True Plot standard impulse response error bands stderr_type: string 'asym': default, computes asymptotic standard errors 'mc': monte carlo standard errors (use rpl) repl: int, default 1000 Number of replications for Monte Carlo and Sims-Zha standard errors seed: int np.random.seed for Monte Carlo replications component: array or vector of principal component indices sFor SVAR system, set orth=Falses"Impulse responses (orthogonalized)sImpulse responses (structural)sImpulse responsesR4tmctsz1tsz2tsz3s<Error type must be either 'asym', 'mc','sz1','sz2', or 'sz3'R-Rtrepltsigniftseedt componenttsubplot_paramst plot_paramst stderr_typeN(R4R5R6R7R8(RRRt ValueErrorR.tFalseRR2t errband_mct err_band_sz1t err_band_sz2t err_band_sz3tplottingt irf_grid_plottnames(R)R-timpulsetresponseR:R>R=t plot_stderrR?R9R;R<RRRRttitletstderrtfig((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pytplot_sT!                       c C sý|r!d} |j} |j} nd} |j} |j} |dkrTtdƒ‚nT|dkru|jd|ƒ}n|dkr¨|jd|d| d|d | ƒ}n|s·d}ntj | ||||j j | d|d | d |d |d |ƒ}|S(s+ Plot cumulative impulse response functions Parameters ---------- orth : bool, default False Compute orthogonalized impulse responses impulse : string or int variable providing the impulse response : string or int variable affected by the impulse signif : float (0 < signif < 1) Significance level for error bars, defaults to 95% CI subplot_params : dict To pass to subplot plotting funcions. Example: if fonts are too big, pass {'fontsize' : 8} or some number to your taste. plot_params : dict plot_stderr: bool, default True Plot standard impulse response error bands stderr_type: string 'asym': default, computes asymptotic standard errors 'mc': monte carlo standard errors (use rpl) repl: int, default 1000 Number of replications for monte carlo standard errors seed: int np.random.seed for Monte Carlo replications s/Cumulative responses responses (orthogonalized)sCumulative responsesR4R5s)`stderr_type` must be one of 'asym', 'mc'R-R9R:R;thlinesR=R>R?(R4R5N( RR#RRR@R3tcum_errband_mcRRFRGRRH(R)R-RIRJR:R>R=RKR?R9R;RLRRRMRN((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pytplot_cum_effects²s."         N( t__name__t __module__t__doc__RRAR,R.R2R3tTrueRORR(((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pyRs  2     P t IRAnalysiscB s=eZdZdddeed„Zed„Zeeddddd„Zeedddddd„Zeedddddd „Z eedddddd „Z d „Z e d „ƒZ d „Zed„Zeddddd„Zed„Zed„Zed„Zed„Zd„Ze d„ƒZd„ZRS(sô Impulse response analysis class. Computes impulse responses, asymptotic standard errors, and produces relevant plots Parameters ---------- model : VAR instance Notes ----- Using Lütkepohl (2005) notation i c C shtj||d|d|d|d|d|ƒ|rC|j|_n |j|_|j|_i|_dS(NRRRRR*(RR,t cov_var_reprtcov_at _cov_alphat _cov_sigmatcov_sigt_g_memo(R)RRRRRR*((s<lib/python2.7/site-packages/statsmodels/tsa/vector_ar/irf.pyR,þs  cC sŸ|r|jƒS|j|jdƒ}tj|jd|jdfƒ|ds  Ù