/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/emplike/ |
H A D | descriptive.py | 272 nobs = self.nobs 324 nobs = self.nobs 356 nobs = self.nobs 388 nobs = self.nobs 511 nobs = self.nobs 865 nobs = self.nobs 870 ((nobs - 2.) * (nobs + 1.) * \ 915 nobs = self.nobs 981 nobs = self.nobs 1087 nobs = self.nobs [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/examples/ |
H A D | try_gof_chisquare.py | 17 nobs = 30000 variable 34 print(np.bincount(rvs) * (1. / nobs)) 38 print(stats.chisquare(freq, nobs*probs)) 39 print('null', chisquare(freq, nobs*probs)) 40 print('delta', chisquare(freq, nobs*probs_d)) 52 chisq, pval = chisquare(freq, nobs*probs_d) 54 print(stats.ncx2.sf(chisq, n_bins, 0.001 * nobs)) 57 print(chisquare(freq, nobs*probs_d, value=np.sqrt(chisq / nobs))) 80 nobs = 3000 variable 85 res1 = chisquare(freq, nobs*probs) [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/distributions/ |
H A D | gof_new.py | 284 mod_factor = np.sqrt(nobs) + 0.12 + 0.11 / np.sqrt(nobs) 295 mod_factor = np.sqrt(nobs) + 0.12 + 0.11 / np.sqrt(nobs) 418 nobs = self.nobs 424 nobs = self.nobs 426 return (cdfvals - np.arange(0.0, nobs)/nobs).max() 440 nobs = self.nobs 449 nobs = self.nobs 457 nobs = self.nobs 468 a = nobs / 4. - 2. / nobs * msum 474 nobs = self.nobs [all …]
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/dports/math/R-cran-gss/gss/R/ |
H A D | ssanova0.R | 15 nobs <- dim(mf)[1] functionVar 35 q <- array(c(q,rk$fun(x,x,nu=i,env=rk$env,out=TRUE)),c(nobs,nobs,nq)) 105 nobs <- length(y) functionVar 107 if (!((dim(s)[1]==nobs)&(dim(q)[1]==nobs)&(dim(q)[2]==nobs) 154 nobs <- length(y) functionVar 157 if (!((dim(s)[1]==nobs)&(dim(q)[1]==nobs)&(dim(q)[2]==nobs) 170 as.integer(nobs), as.integer(nobs), as.integer(nnull), 172 as.integer(nobs), as.integer(nobs), as.integer(nq), 180 double(nobs*nobs*(nq+2)), 225 nobs <- length(obj$c) functionVar [all …]
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H A D | gssanova0.R | 32 nobs <- dim(mf)[1] functionVar 124 nobs <- dim(s)[1] functionVar 126 if (!((dim(s)[1]==nobs)&(dim(q)[1]==nobs)&(dim(q)[2]==nobs) 135 eta <- rep(0,nobs) 245 nobs <- dim(s)[1] functionVar 248 if (!((dim(s)[1]==nobs)&(dim(q)[1]==nobs)&(dim(q)[2]==nobs) 278 as.integer(nobs), as.integer(nobs), as.integer(nq), 286 double(nobs*nobs*(nq+2)), 301 qwk <- array(0,c(nobs,nobs,nq)) 326 as.integer(nobs), as.integer(nobs), as.integer(nq), [all …]
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/dports/math/optpp/optpp-2.4/newmat11/ |
H A D | example.cpp | 28 Matrix X(nobs,npred1); in test1() 36 ColumnVector Y(nobs); Y << y; in test1() 87 Matrix X(nobs,npred); in test2() 94 ColumnVector Y(nobs); Y << y; in test2() 103 Matrix XC(nobs,npred); in test2() 107 ColumnVector YC(nobs); in test2() 164 Matrix X(nobs,npred); in test3() 169 Matrix XC(nobs,npred); in test3() 171 ColumnVector YC(nobs); in test3() 221 Matrix X(nobs,npred1); ColumnVector Y(nobs); in test4() [all …]
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/dports/math/newmat/newmat-1.1_1/ |
H A D | example.cpp | 36 Matrix X(nobs,npred1); in test1() 44 ColumnVector Y(nobs); Y << y; in test1() 95 Matrix X(nobs,npred); in test2() 102 ColumnVector Y(nobs); Y << y; in test2() 111 Matrix XC(nobs,npred); in test2() 115 ColumnVector YC(nobs); in test2() 172 Matrix X(nobs,npred); in test3() 176 Matrix XC(nobs,npred); in test3() 179 ColumnVector YC(nobs); in test3() 229 Matrix X(nobs,npred1); ColumnVector Y(nobs); in test4() [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/distributions/tests/ |
H A D | test_gof_new.py | 9 nobs = 200 12 resu1 = bootstrap(NewNorm(), args=(0, 1), nobs=nobs, nrep=100, 13 value=0.576/(1 + 4./nobs - 25./nobs**2)) 16 tmp = [bootstrap(NewNorm(), args=(0, 1), nobs=nobs, nrep=1) 18 resu2 = (np.array(tmp) > 0.576/(1 + 4./nobs - 25./nobs**2)).mean() 21 tmp = [bootstrap(NewNorm(), args=(0, 1), nobs=nobs, nrep=1, 22 value=0.576/(1 + 4./nobs - 25./nobs**2),
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/dports/finance/R-cran-urca/urca/R/ |
H A D | ur-ers.R | 14 nobs <- length(y) functionVar 15 if(nobs < 50){ 17 }else if(nobs < 100){ 19 }else if(nobs <= 200){ 21 }else if(nobs > 200){ 24 ahat <- 1 - 7.0/nobs 25 ya <- c(y[1], y[2:nobs]-ahat*y[1:(nobs-1)]) 31 ya <- c(y[1], y[2:nobs]-ahat*y[1:(nobs-1)]) 33 trd <- 1:nobs 34 za2 <- c(1, trd[2:nobs]-ahat*trd[1:(nobs-1)]) [all …]
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H A D | ca-po.R | 11 nobs <- nrow(z) functionVar 13 zl <- z[2:nobs,] 14 zr <- z[1:(nobs-1),] 15 nobs <- nobs-1 42 trd <- 1:nobs 45 trd <- 1:(nobs+1) 51 xi2 <- 1/nobs*t(res)%*%res 55 …wsl[x]*(t(res[-c(1:x),])%*%res[-c((nobs-x+1):nobs),] + t(res[-c((nobs-x+1):nobs),])%*%res[-c(1:x)… 61 omega <- xi2 + 1/nobs*smat 63 Mzz <- (1/nobs*t(zl)%*%zl) [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/stats/ |
H A D | power.py | 42 df = nobs - 1 216 df_num = nobs - k_groups 488 colors = rainbow(len(nobs)) 490 for ii, n in enumerate(nobs): 497 colors = rainbow(len(nobs)) 616 nobs=nobs, 790 nobs = nobs1 - ddof 1041 nobs=nobs, 1047 nobs=nobs, 1059 nobs=nobs, [all …]
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H A D | oneway.py | 139 if np.size(nobs) == 1: 140 nobs = np.ones(n_groups) * nobs 142 nobs_t = nobs.sum() 153 weights = nobs / vars_ 163 weights = nobs 440 if nobs is None: 444 ci_f2 = ci_nc / nobs 496 nobs_t = nobs.sum() 502 weights = nobs 552 nobs=nobs, [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/tsa/ |
H A D | diffusion.py | 66 dt = T*1.0/nobs 78 W, t = self.simulateW(nobs=nobs, T=T, dt=dt, nrepl=nrepl) 106 W, t = self.simulateW(nobs=nobs, T=T, dt=dt, nrepl=nrepl) 123 nobs = nobs * Tratio # simple way to change parameter 130 dt = T*1.0/nobs 131 W, t = self.simulateW(nobs=nobs, T=T, dt=dt, nrepl=nrepl) 177 t = np.linspace(ddt, nobs*ddt, nobs) 214 t = np.linspace(ddt, nobs*ddt, nobs) 292 t = np.linspace(ddt, nobs*ddt, nobs) 395 nobs=nobs+1 [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/nonparametric/tests/ |
H A D | test_kernel_regression.py | 13 nobs = 60 72 for i in range(nobs): 139 nobs = 200 158 nobs = 200 181 nobs = 200 206 nobs = 500 226 nobs = 200 241 nobs = 200 262 nobs = 250 286 nobs = 200 [all …]
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/dports/math/R-cran-gss/gss/src/ |
H A D | cdennewton10.f | 9 imu = iwt + nobs 13 iwk = iwtnew + nobs 30 23000 if(.not.(i.le.nobs))goto 23002 39 wtsum = dasum (nobs, wt, 1) 60 23017 if(.not.(k.le.nobs))goto 23019 106 23033 if(.not.(i.le.nobs))goto 23035 128 23044 if(.not.(i.le.nobs))goto 23046 134 call dset (nobs, 1.d0, wt, 1) 136 wtsum = dasum (nobs, wt, 1) 194 call dset (nobs, 1.d0, wt, 1) [all …]
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H A D | reg.f | 13 mu(i) = ddot (nobs, sr(1,i), 1, y, 1) 57 23018 if(.not.(i.le.nobs))goto 23020 63 wk(nobs+1) = ddot (nobs, wk, 1, wk, 1) / dfloat (nobs) 65 23023 if(.not.(i.le.nobs))goto 23025 76 rss = ddot (nobs, y, 1, wk, 1) 78 call dqrdc (sr, nobs, nobs, nnull, wk, idum, dum, 0) 81 call dqrsl (sr, nobs, nobs, nnull, wk, sr(1,nnull+i), dum, sr(1,nn 129 score = rss / dfloat (nobs) * dexp (trc/dfloat(nobs-nnull)) 132 rss = ddot (nobs, wk, 1, wk, 1) / dfloat (nobs) 134 23051 if(.not.(i.le.nobs))goto 23053 [all …]
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H A D | dmudr1.f | 11 *2(nq,*), gwk1(*), gwk2(*), kwk(nobs-nnull,nobs-nnull,*), work1(*), 19 n = nobs - nnull 27 if( lds .lt. nobs .or. nobs .le. n0 .or. n0 .lt. 1 .or. ldqr .lt. 28 *nobs .or. ldqc .lt. nobs .or. nq .le. 0 )then 50 23013 if(.not.(j.le.nobs))goto 23015 58 23019 if(.not.(j.le.nobs))goto 23021 66 call dcopy (nobs, y, 1, ywk, 1) 98 23034 if(.not.(j.le.nobs))goto 23036 109 23042 if(.not.(j.le.nobs))goto 23044 117 call dcopy (nobs, y, 1, ywk, 1) [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/sandbox/nonparametric/ |
H A D | dgp_examples.py | 80 def __init__(self, nobs=200, x=None, distr_x=None, distr_noise=None): argument 84 x = np.random.normal(loc=0, scale=self.s_x, size=nobs) 86 x = distr_x.rvs(size=nobs) 92 noise = np.random.normal(loc=0, scale=self.s_noise, size=nobs) 94 noise = distr_noise.rvs(size=nobs) 157 super(self.__class__, self).__init__(nobs=nobs, x=x, 174 super(self.__class__, self).__init__(nobs=nobs, x=x, 184 def __init__(self, nobs=50, x=None, distr_x=None, distr_noise=None): argument 190 super(self.__class__, self).__init__(nobs=nobs, x=x, 205 nobs = x.shape[0] [all …]
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/dports/math/R-cran-gss/gss/src/ratfor/ |
H A D | cdennewton10.r | 15 imu = iwt + nobs 19 iwk = iwtnew + nobs 46 for (i=1;i<=nobs;i=i+1) { 51 wtsum = dasum (nobs, wt, 1) 55 call dscal (nobs, 1.d0/wtsum, wt, 1) 66 for (k=1;k<=nobs;k=k+1) 92 for (i=1;i<=nobs;i=i+1) { 134 for (i=1;i<=nobs;i=i+1) 153 wtsum = dasum (nobs, wt, 1) 168 for (k=1;k<=nobs;k=k+1) [all …]
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H A D | reg.r | 21 mu(i) = ddot (nobs, sr(1,i), 1, y, 1) 47 for (i=1;i<=nobs;i=i+1) wk(i) = y(i) - ddot (nn, sr(i,1), nobs, dc, 1) 50 wk(nobs+1) = ddot (nobs, wk, 1, wk, 1) / dfloat (nobs) 51 for (i=1;i<=nobs;i=i+1) { 61 rss = ddot (nobs, y, 1, wk, 1) 64 call dqrdc (sr, nobs, nobs, nnull, wk, idum, dum, 0) 66 call dqrsl (sr, nobs, nobs, nnull, wk, sr(1,nnull+i), 92 score = rss / dfloat (nobs) * dexp (trc/dfloat(nobs-nnull)) 97 rss = ddot (nobs, wk, 1, wk, 1) / dfloat (nobs) 99 for (i=1;i<=nobs;i=i+1) { [all …]
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H A D | dmudr1.r | 32 gwk1(*), gwk2(*), kwk(nobs-nnull,nobs-nnull,*),_ 112 n = nobs - nnull 123 if ( lds < nobs | nobs <= n0 | n0 < 1 | ldqr < nobs | ldqc < nobs |_ 141 for (j=1;j<=nobs;j=j+1) call dset (nobs-j+1, 0.d0, qwk(j,j), 1) 143 for (j=1;j<=nobs;j=j+1) 175 for (j=1;j<=nobs;j=j+1) call dset (nobs-j+1, 0.d0, qwk(j,j), 1) 178 for (j=1;j<=nobs;j=j+1) 207 call ddeev (vmu, nobs,_ 289 for (j=1;j<=nobs;j=j+1) call dset (nobs-j+1, 0.d0, qwk(j,j), 1) 292 for (j=1;j<=nobs;j=j+1) [all …]
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/dports/science/dynare/dynare-4.6.4/contrib/dmm/ |
H A D | funct1.for | 74 ALLOCATE(INDT(nt+2),IYK(nobs,ny+1),S(nobs,6)) 76 ALLOCATE(LIKE(nobs),XT(0:nobs,nx),PT(0:nobs,nx,nx), 83 yk(:,J) = U(1+nobs*(J-1):J*nobs) 85 thetaprior(1:nt,3) = U(nobs*(ny+nz)+1:nobs*(ny+nz)+nt) 86 thetaprior(1:nt,4) = U(nobs*(ny+nz)+nt+1:nobs*(ny+nz)+2*nt) 91 IYK(1:nobs,J) = U(I+nobs*(J-1):I+nobs*J-1) 93 I = I+nobs*(ny+1) 95 S(1:nobs,J) = U(I+(J-1)*nobs:I-1+J*nobs) 108 nmis = ny*nobs-SUM(IYK(1:nobs,ny+1)) 128 ALLOCATE(SSMOOTH(nobs,nstot),INN(nobs,ny)) [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tools/ |
H A D | eval_measures.py | 321 nobs = x1.shape[axis] 334 def aic(llf, nobs, df_modelwc): argument 359 def aicc(llf, nobs, df_modelwc): argument 381 return -2.0 * llf + 2.0 * df_modelwc * nobs / (nobs - df_modelwc - 1.0) 384 def bic(llf, nobs, df_modelwc): argument 406 return -2.0 * llf + np.log(nobs) * df_modelwc 409 def hqic(llf, nobs, df_modelwc): argument 491 return sigma2 + aic(0, nobs, df_modelwc) / nobs 525 return sigma2 + aicc(0, nobs, df_modelwc) / nobs 559 return sigma2 + bic(0, nobs, df_modelwc) / nobs [all …]
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/tsa/ |
H A D | _innovations.pyx | 19 nobs : int, optional 54 >>> nobs = activity.shape[0] 55 >>> theta, sigma2 = innovations_algo(acov[:4], nobs=nobs) 63 nobs = int_like(nobs, 'nobs', optional=True) 71 if nobs is not None and nobs < 1: 73 n = acov.shape[0] if nobs is None else nobs 135 >>> theta, sigma2 = innovations_algo(acov[:4], nobs=nobs) 146 nobs = endog.shape[0] 148 if nobs != n_theta: 152 u = np.empty(nobs) [all …]
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H A D | arima_process.py | 189 if nobs > m: 737 self.nobs = nobs 777 nobs=nobs) 817 nobs=nobs, 842 nobs = nobs or model_results.nobs 846 nobs=nobs, 862 return self.__class__(ar, ma, nobs=self.nobs) 877 nobs = nobs or self.nobs 878 return arma_acovf(self.ar, self.ma, nobs=nobs) 896 nobs = nobs or self.nobs [all …]
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