/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/exponential_smoothing/ |
H A D | _ets_smooth.pyx | 86 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 …]
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/dports/science/lammps/lammps-stable_29Sep2021/src/MGPT/ |
H A D | mgpt_splinetab.cpp | 96 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 …]
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/dports/science/PETSc/petsc-3.14.1/src/tao/tutorials/output/ |
H A D | ex4_0.out | 1 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
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H A D | ex4_lmvm_admm_2.out | 8 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
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H A D | ex4_nm_admm_2.out | 8 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
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H A D | ex4_hessian_admm_2.out | 8 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
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H A D | ex4_hessian_admm_1.out | 11 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
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H A D | ex4_lmvm_admm_1.out | 11 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
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H A D | ex4_nm_admm_1.out | 11 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
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H A D | ex4_l1_1.out | 67 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
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H A D | ex4_soft_threshold_admm_1.out | 11 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
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H A D | ex4_lmvm_2.out | 17 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
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H A D | ex4_hessian_2.out | 21 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
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H A D | ex4_hessian_2_alt.out | 20 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
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H A D | ex4_lmvm_1.out | 42 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
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H A D | ex4_nm_1.out | 51 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
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H A D | ex4_nm_2.out | 51 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
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/dports/science/dakota/dakota-6.13.0-release-public.src-UI/packages/external/trilinos/packages/teuchos/numerics/test/DenseMatrix/ |
H A D | cxx_main_solver.cpp | 132 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 …]
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H A D | cxx_main_band_solver.cpp | 141 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 …]
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/dports/math/octave-forge-data-smoothing/data-smoothing/inst/ |
H A D | rgdtsmcore.m | 31 ## @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 …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/tsa/ |
H A D | varma.py | 67 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))
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/dports/math/R/R-4.1.2/src/library/stats/src/ |
H A D | HoltWinters.c | 51 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()
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/dports/math/libRmath/R-4.1.1/src/library/stats/src/ |
H A D | HoltWinters.c | 51 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()
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/dports/astro/astrometry/astrometry.net-0.85/util/ |
H A D | celestial_mechanics.py | 116 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 …]
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/dports/astro/pykep/pykep-2.6/src/third_party/cspice/ |
H A D | dvnorm.c | 16 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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