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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/exponential_smoothing/
H A D_ets_smooth.pyx86 yhat[i] = xhat[prev, 0] + phi * xhat[prev, 1] + xhat[prev, 2+m-1]
91 xhat[i, 1] = (beta_star * (xhat[i, 0] - xhat[prev, 0])
96 xhat[i, 3:] = xhat[prev, 2:2+m-1]
121 yhat[i] = (xhat[prev, 0] + phi * xhat[prev, 1]) * xhat[prev, 2+m-1]
126 xhat[i, 1] = (beta_star * (xhat[i, 0] - xhat[prev, 0])
131 xhat[i, 3:] = xhat[prev, 2:2+m-1]
156 yhat[i] = (xhat[prev, 0] * xhat[prev, 1]**phi) + xhat[prev, 2+m-1]
161 xhat[i, 1] = (beta_star * (xhat[i, 0] / xhat[prev, 0])
166 xhat[i, 3:] = xhat[prev, 2:2+m-1]
191 yhat[i] = (xhat[prev, 0] * xhat[prev, 1]**phi) * xhat[prev, 2+m-1]
[all …]
/dports/science/lammps/lammps-stable_29Sep2021/src/MGPT/
H A Dmgpt_splinetab.cpp96 double xhat,t1,t2,t3; in evalspline() local
100 xhat = (x-x0)/(x1-x0) * n; in evalspline()
102 idx = (int) xhat; in evalspline()
105 xhat = xhat - idx; in evalspline()
109 *y = p[0] + xhat*(p[1] + xhat*(p[2] + xhat*p[3])); in evalspline()
111 *dy = p[1] + xhat*(2*p[2] + xhat*3*p[3]); in evalspline()
117 t1 = p[2] + xhat*p[3]; in evalspline()
118 t2 = p[1] + xhat*t1; in evalspline()
120 t3 = t1 + xhat*p[3]; in evalspline()
122 *y = p[0] + xhat*t2; in evalspline()
[all …]
/dports/science/PETSc/petsc-3.14.1/src/tao/tutorials/output/
H A Dex4_0.out1 J(xhat): 24.5106, predicted: 0.851231, diff 23.6594
2 J(xhat): 6.76613, predicted: 0.851288, diff 5.91484
3 J(xhat): 2.33003, predicted: 0.851317, diff 1.47871
4 J(xhat): 1.22101, predicted: 0.851331, diff 0.369677
5 J(xhat): 0.943758, predicted: 0.851338, diff 0.0924194
6 J(xhat): 0.874447, predicted: 0.851342, diff 0.0231048
7 J(xhat): 0.85712, predicted: 0.851344, diff 0.00577621
8 J(xhat): 0.852789, predicted: 0.851344, diff 0.00144405
9 J(xhat): 0.851706, predicted: 0.851345, diff 0.000361013
10 J(xhat): 0.851435, predicted: 0.851345, diff 9.02533e-05
H A Dex4_lmvm_admm_2.out8 J(xhat): 98.3926, predicted: 4.22724, diff 94.1653
9 J(xhat): 27.7686, predicted: 4.22724, diff 23.5413
10 J(xhat): 10.1126, predicted: 4.22724, diff 5.88533
11 J(xhat): 5.69858, predicted: 4.22724, diff 1.47133
12 J(xhat): 4.59508, predicted: 4.22724, diff 0.367833
13 J(xhat): 4.3192, predicted: 4.22724, diff 0.0919583
14 J(xhat): 4.25023, predicted: 4.22724, diff 0.0229896
15 J(xhat): 4.23299, predicted: 4.22724, diff 0.0057474
16 J(xhat): 4.22868, predicted: 4.22724, diff 0.00143685
17 J(xhat): 4.2276, predicted: 4.22724, diff 0.000359212
H A Dex4_nm_admm_2.out8 J(xhat): 98.3842, predicted: 4.21886, diff 94.1653
9 J(xhat): 27.7644, predicted: 4.22306, diff 23.5413
10 J(xhat): 10.1105, predicted: 4.22516, diff 5.88533
11 J(xhat): 5.69755, predicted: 4.22621, diff 1.47133
12 J(xhat): 4.59457, predicted: 4.22674, diff 0.367833
13 J(xhat): 4.31896, predicted: 4.227, diff 0.0919583
14 J(xhat): 4.25012, predicted: 4.22713, diff 0.0229896
15 J(xhat): 4.23295, predicted: 4.2272, diff 0.0057474
16 J(xhat): 4.22867, predicted: 4.22723, diff 0.00143685
17 J(xhat): 4.22761, predicted: 4.22725, diff 0.000359212
H A Dex4_hessian_admm_2.out8 J(xhat): 98.3926, predicted: 4.22724, diff 94.1653
9 J(xhat): 27.7686, predicted: 4.22724, diff 23.5413
10 J(xhat): 10.1126, predicted: 4.22724, diff 5.88533
11 J(xhat): 5.69858, predicted: 4.22724, diff 1.47133
12 J(xhat): 4.59508, predicted: 4.22724, diff 0.367833
13 J(xhat): 4.3192, predicted: 4.22724, diff 0.0919583
14 J(xhat): 4.25023, predicted: 4.22724, diff 0.0229896
15 J(xhat): 4.23299, predicted: 4.22724, diff 0.0057474
16 J(xhat): 4.22868, predicted: 4.22724, diff 0.00143685
17 J(xhat): 4.2276, predicted: 4.22724, diff 0.000359212
H A Dex4_hessian_admm_1.out11 J(xhat): 108.714, predicted: 20.6301, diff 88.084
12 J(xhat): 40.4056, predicted: 16.3031, diff 24.1026
13 J(xhat): 21.2033, predicted: 14.1395, diff 7.06373
14 J(xhat): 15.3401, predicted: 13.0578, diff 2.28228
15 J(xhat): 13.343, predicted: 12.5169, diff 0.826056
16 J(xhat): 12.578, predicted: 12.2465, diff 0.331564
17 J(xhat): 12.254, predicted: 12.1112, diff 0.142725
18 J(xhat): 12.1065, predicted: 12.0436, diff 0.0629062
19 J(xhat): 12.0365, predicted: 12.0098, diff 0.0266843
20 J(xhat): 12.004, predicted: 11.9929, diff 0.011123
H A Dex4_lmvm_admm_1.out11 J(xhat): 113.776, predicted: 9.65716, diff 104.119
12 J(xhat): 42.424, predicted: 10.6285, diff 31.7955
13 J(xhat): 21.7109, predicted: 11.1142, diff 10.5968
14 J(xhat): 15.0924, predicted: 11.357, diff 3.73537
15 J(xhat): 12.7926, predicted: 11.4784, diff 1.3142
16 J(xhat): 11.9717, predicted: 11.5391, diff 0.432627
17 J(xhat): 11.7068, predicted: 11.5695, diff 0.137322
18 J(xhat): 11.6271, predicted: 11.5846, diff 0.0424309
19 J(xhat): 11.6049, predicted: 11.5922, diff 0.0127121
20 J(xhat): 11.5994, predicted: 11.596, diff 0.00334437
H A Dex4_nm_admm_1.out11 J(xhat): 112.879, predicted: 9.66734, diff 103.212
12 J(xhat): 41.9672, predicted: 10.4993, diff 31.4679
13 J(xhat): 21.4653, predicted: 10.9153, diff 10.55
14 J(xhat): 14.9669, predicted: 11.1233, diff 3.84363
15 J(xhat): 12.6557, predicted: 11.2273, diff 1.42842
16 J(xhat): 11.7559, predicted: 11.2793, diff 0.476597
17 J(xhat): 11.4357, predicted: 11.3053, diff 0.130448
18 J(xhat): 11.3475, predicted: 11.3183, diff 0.0292416
19 J(xhat): 11.3309, predicted: 11.3248, diff 0.00615894
20 J(xhat): 11.3306, predicted: 11.328, diff 0.00255596
H A Dex4_l1_1.out67 J(xhat): 97.3893, predicted: 7.1005, diff 90.2888
68 J(xhat): 33.1988, predicted: 7.14707, diff 26.0517
69 J(xhat): 15.423, predicted: 7.17035, diff 8.25269
70 J(xhat): 10.1151, predicted: 7.182, diff 2.93305
71 J(xhat): 8.35602, predicted: 7.18782, diff 1.1682
72 J(xhat): 7.70025, predicted: 7.19073, diff 0.509521
73 J(xhat): 7.4283, predicted: 7.19218, diff 0.236116
74 J(xhat): 7.30631, predicted: 7.19291, diff 0.113396
75 J(xhat): 7.24881, predicted: 7.19327, diff 0.0555329
76 J(xhat): 7.22093, predicted: 7.19346, diff 0.0274751
H A Dex4_soft_threshold_admm_1.out11 J(xhat): 113.626, predicted: 16.5257, diff 97.1007
12 J(xhat): 42.3779, predicted: 13.8019, diff 28.576
13 J(xhat): 21.7055, predicted: 12.44, diff 9.26546
14 J(xhat): 15.1072, predicted: 11.759, diff 3.34818
15 J(xhat): 12.7449, predicted: 11.4186, diff 1.32637
16 J(xhat): 11.801, predicted: 11.2483, diff 0.55267
17 J(xhat): 11.3905, predicted: 11.1632, diff 0.227268
18 J(xhat): 11.2058, predicted: 11.1206, diff 0.0851946
19 J(xhat): 11.1289, predicted: 11.0994, diff 0.0295115
20 J(xhat): 11.1013, predicted: 11.0887, diff 0.0125992
H A Dex4_lmvm_2.out17 J(xhat): 98.3927, predicted: 4.22739, diff 94.1653
18 J(xhat): 27.7687, predicted: 4.22732, diff 23.5413
19 J(xhat): 10.1126, predicted: 4.22728, diff 5.88533
20 J(xhat): 5.6986, predicted: 4.22726, diff 1.47133
21 J(xhat): 4.59509, predicted: 4.22725, diff 0.367833
22 J(xhat): 4.31921, predicted: 4.22725, diff 0.0919583
23 J(xhat): 4.25024, predicted: 4.22725, diff 0.0229896
24 J(xhat): 4.23299, predicted: 4.22724, diff 0.0057474
25 J(xhat): 4.22868, predicted: 4.22724, diff 0.00143685
26 J(xhat): 4.2276, predicted: 4.22724, diff 0.000359212
H A Dex4_hessian_2.out21 J(xhat): 98.3926, predicted: 4.22724, diff 94.1653
22 J(xhat): 27.7686, predicted: 4.22724, diff 23.5413
23 J(xhat): 10.1126, predicted: 4.22724, diff 5.88533
24 J(xhat): 5.69858, predicted: 4.22724, diff 1.47133
25 J(xhat): 4.59508, predicted: 4.22724, diff 0.367833
26 J(xhat): 4.3192, predicted: 4.22724, diff 0.0919583
27 J(xhat): 4.25023, predicted: 4.22724, diff 0.0229896
28 J(xhat): 4.23299, predicted: 4.22724, diff 0.0057474
29 J(xhat): 4.22868, predicted: 4.22724, diff 0.00143685
30 J(xhat): 4.2276, predicted: 4.22724, diff 0.000359212
H A Dex4_hessian_2_alt.out20 J(xhat): 98.3926, predicted: 4.22725, diff 94.1653
21 J(xhat): 27.7686, predicted: 4.22724, diff 23.5413
22 J(xhat): 10.1126, predicted: 4.22724, diff 5.88533
23 J(xhat): 5.69858, predicted: 4.22724, diff 1.47133
24 J(xhat): 4.59508, predicted: 4.22724, diff 0.367834
25 J(xhat): 4.3192, predicted: 4.22724, diff 0.091959
26 J(xhat): 4.25023, predicted: 4.22724, diff 0.0229907
27 J(xhat): 4.23299, predicted: 4.22724, diff 0.0057478
28 J(xhat): 4.22868, predicted: 4.22724, diff 0.00143766
29 J(xhat): 4.2276, predicted: 4.22724, diff 0.000360012
H A Dex4_lmvm_1.out42 J(xhat): 112.439, predicted: 10.6288, diff 101.81
43 J(xhat): 41.665, predicted: 10.6959, diff 30.9691
44 J(xhat): 21.23, predicted: 10.7295, diff 10.5005
45 J(xhat): 14.7504, predicted: 10.7462, diff 4.00416
46 J(xhat): 12.4451, predicted: 10.7546, diff 1.69048
47 J(xhat): 11.5261, predicted: 10.7588, diff 0.767267
48 J(xhat): 11.125, predicted: 10.7609, diff 0.364065
49 J(xhat): 10.939, predicted: 10.762, diff 0.177065
50 J(xhat): 10.8497, predicted: 10.7625, diff 0.0872158
51 J(xhat): 10.8059, predicted: 10.7627, diff 0.0432037
H A Dex4_nm_1.out51 J(xhat): 94.821, predicted: -30.6357, diff 125.457
52 J(xhat): 34.3972, predicted: -8.39532, diff 42.7925
53 J(xhat): 19.1371, predicted: 2.72486, diff 16.4123
54 J(xhat): 15.2451, predicted: 8.28495, diff 6.96015
55 J(xhat): 14.2336, predicted: 11.065, diff 3.16858
56 J(xhat): 13.9614, predicted: 12.455, diff 1.50641
57 J(xhat): 13.8838, predicted: 13.15, diff 0.733739
58 J(xhat): 13.8595, predicted: 13.4975, diff 0.362002
59 J(xhat): 13.8511, predicted: 13.6713, diff 0.179784
60 J(xhat): 13.8478, predicted: 13.7582, diff 0.089588
H A Dex4_nm_2.out51 J(xhat): 63.4419, predicted: -30.7234, diff 94.1653
52 J(xhat): 14.4411, predicted: -9.10021, diff 23.5413
53 J(xhat): 7.59672, predicted: 1.71139, diff 5.88533
54 J(xhat): 8.58853, predicted: 7.11719, diff 1.47133
55 J(xhat): 10.1879, predicted: 9.82009, diff 0.367833
56 J(xhat): 11.2635, predicted: 11.1715, diff 0.0919583
57 J(xhat): 11.8703, predicted: 11.8473, diff 0.0229896
58 J(xhat): 12.1909, predicted: 12.1851, diff 0.0057474
59 J(xhat): 12.3555, predicted: 12.3541, diff 0.00143685
60 J(xhat): 12.4389, predicted: 12.4385, diff 0.000359212
/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/trilinos/packages/teuchos/numerics/test/DenseMatrix/
H A Dcxx_main_solver.cpp132 DVector xhat(n), b(n), bt(n); in main() local
151 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
172 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
182 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
223 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
250 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
260 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
277 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
308 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
318 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
[all …]
H A Dcxx_main_band_solver.cpp141 DVector xhat(n), b(n), bt(n); in main() local
174 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
192 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
202 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
220 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
258 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
268 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
285 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
326 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
336 xhat.putScalar( ScalarTraits<STYPE>::zero() ); in main()
[all …]
/dports/math/octave-forge-data-smoothing/data-smoothing/inst/
H A Drgdtsmcore.m31 ## @item "xhat", @var{vector}
57 xhat = x; variable
68 case "xhat"
70 xhat = varargin{i+1}; variable
93 Nhat = length(xhat);
95 ## test that xhat is increasing
96 if !all(diff(xhat)>0)
103 ## test that xhat spans x
104 if ( min(x) < min(xhat) || max(xhat) < max(x) )
110 idx = interp1(xhat,1:Nhat,x,"nearest"); # works for unequally spaced xhat
[all …]
/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/tsa/
H A Dvarma.py67 xhat = np.zeros(x.shape)
73 xhat[t,:] = const + (x[t-p:t,:,np.newaxis]*B).sum(axis=1).sum(axis=0)
74 return xhat
90 xhat = np.zeros(x.shape)
98 xhat[t,:] = const + (x[t-P:t,:,np.newaxis]*B).sum(axis=1).sum(axis=0) + \
100 e[t,:] = x[t,:] - xhat[t,:]
101 return xhat, e
115 xhat = VAR(x,B) variable
116 print(np.all(xhat[P:,0]==np.correlate(x[:-1,0],np.ones(P))*2))
/dports/math/R/R-4.1.2/src/library/stats/src/
H A DHoltWinters.c51 double res = 0, xhat = 0, stmp = 0; in HoltWinters() local
65 xhat = level[i0 - 1] + (*dotrend == 1 ? trend[i0 - 1] : 0); in HoltWinters()
68 xhat += stmp; in HoltWinters()
70 xhat *= stmp; in HoltWinters()
73 res = x[i] - xhat; in HoltWinters()
/dports/math/libRmath/R-4.1.1/src/library/stats/src/
H A DHoltWinters.c51 double res = 0, xhat = 0, stmp = 0; in HoltWinters() local
65 xhat = level[i0 - 1] + (*dotrend == 1 ? trend[i0 - 1] : 0); in HoltWinters()
68 xhat += stmp; in HoltWinters()
70 xhat *= stmp; in HoltWinters()
73 res = x[i] - xhat; in HoltWinters()
/dports/astro/astrometry/astrometry.net-0.85/util/
H A Dcelestial_mechanics.py116 yhat = np.cross(zhat, xhat)
117 return (xhat, yhat, zhat)
119 def position_from_orbital_vectors(xhat, yhat, a, e, M): argument
124 x = a * (cosE - e) * xhat + b * sinE * yhat
148 x = a * (cosE - e) * xhat + b * sinE * yhat
150 v = -a * sinE * dEdt * xhat + b * cosE * dEdt * yhat
179 xhat = np.cross(jhat, zhat)
180 xhat /= norm1d(xhat)
182 xhat = evec / e
183 yhat = np.cross(zhat, xhat)
[all …]
/dports/astro/pykep/pykep-2.6/src/third_party/cspice/
H A Ddvnorm.c16 doublereal xhat[3]; in dvnorm_() local
243 vhat_(state, xhat); in dvnorm_()
251 ret_val = vdot_(&state[3], xhat); in dvnorm_()

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