from numpy import array from statsmodels.tools.testing import Holder mlpacf = Holder() mlpacf.comment = 'mlab.parcorr(x, [], 2, nout=3)' mlpacf.name = 'mlpacf' mlpacf.lags1000 = array([ [0.], [1.], [2.], [3.], [4.], [5.], [6.], [7.], [8.], [9.], [10.], [11.], [12.], [13.], [14.], [15.], [16.], [17.], [18.], [19.], [20.]]) mlpacf.bounds1000 = array([ [0.06334064], [-0.06334064]]) mlpacf.lags100 = array([ [0.], [1.], [2.], [3.], [4.], [5.], [6.], [7.], [8.], [9.], [10.], [11.], [12.], [13.], [14.], [15.], [16.], [17.], [18.], [19.], [20.]]) mlpacf.pacf100 = array([ [1.], [0.47253777], [-0.49466966], [-0.02689319], [-0.00122204], [0.08419183], [0.03220774], [0.10404012], [0.05304617], [-0.04129564], [-0.04049451], [0.11727754], [0.11804158], [-0.05864957], [-0.15681802], [0.11828684], [0.05156002], [0.00694629], [0.01668964], [0.02236851], [-0.0909443]]) mlpacf.pacf1000 = array([ [1.00000000e+00], [5.29288262e-01], [-5.31849027e-01], [1.17440051e-02], [-5.37941905e-02], [-4.11119348e-02], [-2.40367432e-02], [2.24289891e-02], [3.33007235e-02], [4.59658302e-02], [6.65850553e-03], [-3.76714278e-02], [5.27229738e-02], [2.50796558e-02], [-4.42597301e-02], [-1.95819186e-02], [4.70451394e-02], [-1.70963705e-03], [3.04262524e-04], [-6.22001614e-03], [-1.16694989e-02]]) mlpacf.bounds100 = array([ [0.20306923], [-0.20306923]]) mlacf = Holder() mlacf.comment = 'mlab.autocorr(x, [], 2, nout=3)' mlacf.name = 'mlacf' mlacf.acf1000 = array([ [1.], [0.5291635], [-0.10186759], [-0.35798372], [-0.25894203], [-0.06398397], [0.0513664], [0.08222289], [0.08115406], [0.07674254], [0.04540619], [-0.03024699], [-0.05886634], [-0.01422948], [0.01277825], [-0.01013384], [-0.00765693], [0.02183677], [0.03618889], [0.01622553], [-0.02073507]]) mlacf.lags1000 = array([ [0.], [1.], [2.], [3.], [4.], [5.], [6.], [7.], [8.], [9.], [10.], [11.], [12.], [13.], [14.], [15.], [16.], [17.], [18.], [19.], [20.]]) mlacf.bounds1000 = array([ [0.0795181], [-0.0795181]]) mlacf.lags100 = array([ [0.], [1.], [2.], [3.], [4.], [5.], [6.], [7.], [8.], [9.], [10.], [11.], [12.], [13.], [14.], [15.], [16.], [17.], [18.], [19.], [20.]]) mlacf.bounds100 = array([ [0.24319646], [-0.24319646]]) mlacf.acf100 = array([ [1.], [0.47024791], [-0.1348087], [-0.32905777], [-0.18632437], [0.06223404], [0.16645194], [0.12589966], [0.04805397], [-0.03785273], [-0.0956997], [0.00644021], [0.17157144], [0.12370327], [-0.07597526], [-0.13865131], [0.02730275], [0.13624193], [0.10417949], [0.01114516], [-0.09727938]]) mlccf = Holder() mlccf.comment = 'mlab.crosscorr(x[4:], x[:-4], [], 2, nout=3)' mlccf.name = 'mlccf' mlccf.ccf100 = array([ [0.20745123], [0.12351939], [-0.03436893], [-0.14550879], [-0.10570855], [0.0108839], [0.1108941], [0.14562415], [0.02872607], [-0.14976649], [-0.08274954], [0.13158485], [0.18350343], [0.00633845], [-0.10359988], [-0.0416147], [0.05056298], [0.13438945], [0.17832125], [0.06665153], [-0.19999538], [-0.31700548], [-0.09727956], [0.46547234], [0.92934645], [0.44480271], [-0.09228691], [-0.21627289], [-0.05447732], [0.13786254], [0.15409039], [0.07466298], [-0.01000896], [-0.06744264], [-0.0607185], [0.04338471], [0.12336618], [0.07712367], [-0.08739259], [-0.09319212], [0.04426167]]) mlccf.lags1000 = array([ [-20.], [-19.], [-18.], [-17.], [-16.], [-15.], [-14.], [-13.], [-12.], [-11.], [-10.], [-9.], [-8.], [-7.], [-6.], [-5.], [-4.], [-3.], [-2.], [-1.], [0.], [1.], [2.], [3.], [4.], [5.], [6.], [7.], [8.], [9.], [10.], [11.], [12.], [13.], [14.], [15.], [16.], [17.], [18.], [19.], [20.]]) mlccf.bounds1000 = array([ [0.06337243], [-0.06337243]]) mlccf.ccf1000 = array([ [0.02733339], [0.04372407], [0.01082335], [-0.02755073], [-0.02076039], [0.01624263], [0.03622844], [0.02186092], [-0.00766506], [-0.0101448], [0.01279167], [-0.01424596], [-0.05893064], [-0.03028013], [0.04545462], [0.076825], [0.08124118], [0.08231121], [0.05142144], [-0.06405412], [-0.25922346], [-0.35806674], [-0.1017256], [0.5293535], [0.99891094], [0.52941977], [-0.10127572], [-0.35691466], [-0.25943369], [-0.06458511], [0.05026194], [0.08196501], [0.08242852], [0.07775845], [0.04590431], [-0.03195209], [-0.06162966], [-0.01395345], [0.01448736], [-0.00952503], [-0.00927344]]) mlccf.lags100 = array([ [-20.], [-19.], [-18.], [-17.], [-16.], [-15.], [-14.], [-13.], [-12.], [-11.], [-10.], [-9.], [-8.], [-7.], [-6.], [-5.], [-4.], [-3.], [-2.], [-1.], [0.], [1.], [2.], [3.], [4.], [5.], [6.], [7.], [8.], [9.], [10.], [11.], [12.], [13.], [14.], [15.], [16.], [17.], [18.], [19.], [20.]]) mlccf.bounds100 = array([ [0.20412415], [-0.20412415]]) mlywar = Holder() mlywar.comment = "mlab.ar(x100-x100.mean(), 10, 'yw').a.ravel()" mlywar.arcoef100 = array([ 1., -0.66685531, 0.43519425, -0.00399862, 0.05521524, -0.09366752, 0.01093454, -0.00688404, -0.04739089, 0.00127931, 0.03946846]) mlywar.arcoef1000 = array([ 1., -0.81230253, 0.55766432, -0.02370962, 0.02688963, 0.01110911, 0.02239171, -0.01891209, -0.00240527, -0.01752532, -0.06348611, 0.0609686, -0.00717163, -0.0467326, -0.00122755, 0.06004768, -0.04893984, 0.00575949, 0.00249315, -0.00560358, 0.01248498]) mlywar.name = 'mlywar'