File: t_InverseBoxCoxTransform_std.expout

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myInverseBoxCox= InverseBoxCox(lambda=[0.2], shift=[0])
myInverseBoxCox input dimension =  1
myInverseBoxCox output dimension =  1
input time series =
     [ t          X0         ]
 0 : [  0          0.259753  ]
 1 : [  0.1        0.76561   ]
 2 : [  0.2       -0.729447  ]
 3 : [  0.3       -0.934994  ]
 4 : [  0.4       -0.305886  ]
 5 : [  0.5        0.938846  ]
 6 : [  0.6        0.841359  ]
 7 : [  0.7        0.0060803 ]
 8 : [  0.8       -0.873588  ]
 9 : [  0.9       -0.414486  ]
10 : [  1          0.428764  ]
11 : [  1.1       -0.233276  ]
12 : [  1.2       -0.252465  ]
13 : [  1.3        0.474536  ]
14 : [  1.4        0.767007  ]
15 : [  1.5       -0.410012  ]
16 : [  1.6        0.857021  ]
17 : [  1.7        0.641622  ]
18 : [  1.8        0.36915   ]
19 : [  1.9        0.656054  ]
20 : [  2         -0.280396  ]
21 : [  2.1        0.909492  ]
22 : [  2.2        0.177231  ]
23 : [  2.3       -0.635922  ]
24 : [  2.4       -0.82843   ]
25 : [  2.5        0.321455  ]
26 : [  2.6       -0.579116  ]
27 : [  2.7       -0.227543  ]
28 : [  2.8       -0.950881  ]
29 : [  2.9       -0.162163  ]
30 : [  3          0.963682  ]
31 : [  3.1        0.832264  ]
32 : [  3.2        0.911206  ]
33 : [  3.3       -0.0540999 ]
34 : [  3.4       -0.480278  ]
35 : [  3.5        0.32268   ]
36 : [  3.6       -0.0204509 ]
37 : [  3.7       -0.0629513 ]
38 : [  3.8       -0.777844  ]
39 : [  3.9       -0.309362  ]
40 : [  4          0.311954  ]
41 : [  4.1        0.350177  ]
42 : [  4.2        0.95796   ]
43 : [  4.3        0.292669  ]
44 : [  4.4       -0.871575  ]
45 : [  4.5        0.546039  ]
46 : [  4.6        0.988399  ]
47 : [  4.7       -0.833853  ]
48 : [  4.8       -0.550266  ]
49 : [  4.9       -0.394761  ]
50 : [  5         -0.565578  ]
output time series = 
     [ t        y0       ]
 0 : [ 0        1.28818  ]
 1 : [ 0.1      2.03881  ]
 2 : [ 0.2      0.454538 ]
 3 : [ 0.3      0.355186 ]
 4 : [ 0.4      0.72932  ]
 5 : [ 0.5      2.36407  ]
 6 : [ 0.6      2.1763   ]
 7 : [ 0.7      1.0061   ]
 8 : [ 0.8      0.382836 ]
 9 : [ 0.9      0.648769 ]
10 : [ 1        1.50888  ]
11 : [ 1.1      0.787499 ]
12 : [ 1.2      0.771775 ]
13 : [ 1.3      1.57357  ]
14 : [ 1.4      2.04128  ]
15 : [ 1.5      0.65194  ]
16 : [ 1.6      2.20564  ]
17 : [ 1.7      1.82881  ]
18 : [ 1.8      1.42783  ]
19 : [ 1.9      1.85233  ]
20 : [ 2        0.749338 ]
21 : [ 2.1      2.30622  ]
22 : [ 2.2      1.19025  ]
23 : [ 2.3      0.506539 ]
24 : [ 2.4      0.404248 ]
25 : [ 2.5      1.36553  ]
26 : [ 2.6      0.540375 ]
27 : [ 2.7      0.792246 ]
28 : [ 2.8      0.348299 ]
29 : [ 2.9      0.848021 ]
30 : [ 3        2.41392  ]
31 : [ 3.1      2.15941  ]
32 : [ 3.2      2.30957  ]
33 : [ 3.3      0.947058 ]
34 : [ 3.4      0.603544 ]
35 : [ 3.5      1.3671   ]
36 : [ 3.6      0.979716 ]
37 : [ 3.7      0.938614 ]
38 : [ 3.8      0.42936  ]
39 : [ 3.9      0.726624 ]
40 : [ 4        1.35339  ]
41 : [ 4.1      1.40278  ]
42 : [ 4.2      2.40236  ]
43 : [ 4.3      1.329    ]
44 : [ 4.4      0.383771 ]
45 : [ 4.5      1.67905  ]
46 : [ 4.6      2.46436  ]
47 : [ 4.7      0.401627 ]
48 : [ 4.8      0.558239 ]
49 : [ 4.9      0.662843 ]
50 : [ 5        0.5487   ]
gradient= [[ 0.0625 ]]
hessian= sheet #0
[[ 0.1 ]]
myBoxCox =  BoxCox(lambda=[0.2], shift=[0])
number of call(s) :  51