ó áp7]c@`sfdZddlmZmZmZddlZddlZddlZddl Z ddl Z ddl m Z ddlmZmZmZddlmZmZddlmZdd lmZmZmZmZejjejjeƒƒZ ejj!d d ƒZ"e j#ejj!e e"ƒƒZ$d e%fd „ƒYZ&de&fd„ƒYZ'de&fd„ƒYZ(e j)j*dƒde&fd„ƒYƒZ+de&fd„ƒYZ,de&fd„ƒYZ-de&fd„ƒYZ.de.fd„ƒYZ/de.fd„ƒYZ0de.fd „ƒYZ1d!e&fd"„ƒYZ2d#e%fd$„ƒYZ3d%e3fd&„ƒYZ4d'e3fd(„ƒYZ5d)e3fd*„ƒYZ6d+e6fd,„ƒYZ7d-e6fd.„ƒYZ8d/e6fd0„ƒYZ9d1e3fd2„ƒYZ:d3e3fd4„ƒYZ;d5„Z<d6„Z=d7„Z>d8„Z?d9„Z@d:„ZAd;„ZBd<„ZCd=„ZDd>„ZEd?„ZFd@„ZGdA„ZHdS(Bs? Tests for python wrapper of state space representation and filtering Author: Chad Fulton License: Simplified-BSD References ---------- Kim, Chang-Jin, and Charles R. Nelson. 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications". MIT Press Books. The MIT Press. i(tdivisiontabsolute_importtprint_functionN(tRepresentation(t KalmanFiltert FilterResultstPredictionResults(ttoolstsarimaxi(tresults_kalman_filter(t assert_equaltassert_almost_equalt assert_raisestassert_allclosetresultssresults_clark1989_R.csvt Clark1987cB`sAeZdZeed„ƒZed„ƒZd„Zd„ZRS(s> Clark's (1987) univariate unobserved components model of real GDP (as presented in Kim and Nelson, 1999) Test data produced using GAUSS code described in Kim and Nelson (1999) and found at http://econ.korea.ac.kr/~cjkim/SSMARKOV.htm See `results.results_kalman_filter` for more information. c K`stj|_tj|jdƒ|_tj|jddtjddddƒdd gƒ}tj|d ƒ|d RDRG(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR&s  , tTestClark1987SinglecB`seZdZed„ƒZRS(sP Basic single precision test for the loglikelihood and filtered states. cC`sBtjdƒtt|ƒjdtjddƒ|jƒ|_dS(NsNot implementedRtconserve_memoryi( tpytesttskiptsuperRMR<R"tfloat32R>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<{s (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRMwstTestClark1987DoublecB`seZdZed„ƒZRS(sP Basic double precision test for the loglikelihood and filtered states. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNi(RQRSR<RLR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<ˆs (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRS„ssNot implementedtTestClark1987SingleComplexcB`seZdZed„ƒZRS(s\ Basic single precision complex test for the loglikelihood and filtered states. cC`s5tt|ƒjdtjddƒ|jƒ|_dS(NRRNi(RQRTR<R"t complex64R>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<–s(RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRTstTestClark1987DoubleComplexcB`seZdZed„ƒZRS(s\ Basic double precision complex test for the loglikelihood and filtered states. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNi(RQRVR<tcomplexR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<£s (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRVžstTestClark1987ConservecB`seZdZed„ƒZRS(sM Memory conservation test for the loglikelihood and filtered states. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNiii(RQRXR<RLR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<¯s (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRX«stClark1987ForecastcB`s/eZdZeeddd„ƒZd„ZRS(sE Forecasting test for the loglikelihood and filtered states. idicC`s™tt|ƒjd|d|ƒ||_tjtj|jjddd…ftj g|fddd|ddƒ|j_|jjj d|j_ dS( NRRNitndminitordertFi( RQRYR<t nforecastR"R+tr_R$tendogtnantshapetnobs(R3RR]RN((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<»s  3cC`sÊt|jjd|jd|j !|jjdd…dfdƒt|jjd|jd|j !|jjdd…dfdƒt|jjd|jd|j !|jjdd…dfdƒdS(NiR?iiii(R RRERR]R RF(RC((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRGÉs  (RHRIRJRKRLR<RG(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRY·s tTestClark1987ForecastDoublecB`seZdZed„ƒZRS(sR Basic double forecasting test for the loglikelihood and filtered states. cC`s&tt|ƒjƒ|jƒ|_dS(N(RQRcR<R>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<Üs(RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRcØst"TestClark1987ForecastDoubleComplexcB`seZdZed„ƒZRS(s^ Basic double complex forecasting test for the loglikelihood and filtered states. cC`s,tt|ƒjdtƒ|jƒ|_dS(NR(RQRdR<RWR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<çs(RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRdâstTestClark1987ForecastConservecB`seZdZed„ƒZRS(s] Memory conservation forecasting test for the loglikelihood and filtered states. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNiii(RQReR<RLR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<ôs (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyReïstTestClark1987ConserveAllcB`s/eZdZed„ƒZd„Zd„ZRS(s] Memory conservation forecasting test for the loglikelihood and filtered states. cC`sEtt|ƒjdtdd ƒ|jd|j_|jƒ|_dS( NRRNiiiiR?iii( RQRfR<RLRR$tloglikelihood_burnR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<s cC`s%t|jjd|jddƒdS(NiR@i(R 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Test data produced using GAUSS code described in Kim and Nelson (1999) and found at http://econ.korea.ac.kr/~cjkim/SSMARKOV.htm See `results.results_kalman_filter` for more information. c K`sNtj|_tj|jdƒ|_tj|jddtjddddƒdd d gƒd }tj|d ƒ|d <|d d |d [scC`s+t|jjdjƒ|jddƒdS(NiR@i(R RRARBR(RC((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRD`scC`sðt|jjd|jd|jjdd…dfdƒt|jjd|jd|jjdd…dfdƒt|jjd|jd|jjdd…dfdƒt|jjd|jd|jjdd…dfdƒdS(NiR?iiiii(R RRERR RF(RC((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRGgs   ( RHRIRJRKRLR<R>RDRG(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRis  4 t TestClark1989cB`s&eZdZed„ƒZd„ZRS(s| Basic double precision test for the loglikelihood and filtered states with two-dimensional observation vector. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNi(RQRsR<RLR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<scC`s9t|jjjddƒjddƒtdddƒdS(NtaxisiitV1tatolg-Cëâ6?(R Rt kalman_gainRBtclark1989_results(RC((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyttest_kalman_gain„s$(RHRIRJRKR<Ry(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRszstTestClark1989ConservecB`seZdZed„ƒZRS(sy Memory conservation test for the loglikelihood and filtered states with two-dimensional observation vector. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNiii(RQRzR<RLR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<Žs (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRz‰stClark1989ForecastcB`s/eZdZeeddd„ƒZd„ZRS(sy Memory conservation test for the loglikelihood and filtered states with two-dimensional observation vector. idicC`s±tt|ƒjd|d|ƒ||_tjtj|jjtj tj tj g|j d|ƒfddd|ddƒ|j_|jjj d|j_ |jƒ|_dS(NRRNiRZR[R\i(RQR{R<R]R"R+tc_R$R_R^R`treshapeRaRbR>R(R3RR]RN((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<›s   -cC`s t|jjd|jd|j !|jjdd…dfdƒt|jjd|jd|j !|jjdd…dfdƒt|jjd|jd|j !|jjdd…dfdƒt|jjd|jd|j !|jjdd…dfdƒdS(NiR?iiiii(R RRERR]R RF(RC((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRG®s   (RHRIRJRKRLR<RG(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR{–stTestClark1989ForecastDoublecB`seZdZed„ƒZRS(sR Basic double forecasting test for the loglikelihood and filtered states. cC`s&tt|ƒjƒ|jƒ|_dS(N(RQR~R<R>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<Ås(RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR~Ást"TestClark1989ForecastDoubleComplexcB`seZdZed„ƒZRS(s^ Basic double complex forecasting test for the loglikelihood and filtered states. cC`s,tt|ƒjdtƒ|jƒ|_dS(NR(RQRR<RWR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<Ðs(RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyRËstTestClark1989ForecastConservecB`seZdZed„ƒZRS(s] Memory conservation forecasting test for the loglikelihood and filtered states. cC`s2tt|ƒjdtddƒ|jƒ|_dS(NRRNiii(RQR€R<RLR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<Ýs (RHRIRJRKR<(((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR€ØstTestClark1989ConserveAllcB`s/eZdZed„ƒZd„Zd„ZRS(s] Memory conservation forecasting test for the loglikelihood and filtered states. cC`s>tt|ƒjdtdd ƒd|j_|jƒ|_dS( NRRNiiiiiiii(RQRR<RLR$RgR>R(R3((sSlib/python2.7/site-packages/statsmodels/tsa/statespace/tests/test_representation.pyR<ês  cC`s%t|jjd|jddƒdS(NiR@i(R 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