Repository URL to install this package:
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Version:
0.3.1 ▾
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import numpy as np
from numpy import array
class Holder(object):
pass
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'