/dports/math/R-cran-survey/survey/tests/ |
H A D | contrast-replicates.R | 8 meanlogs_without<-svyby(~log(enroll),~stype,svymean, design=rclus1,covmat=TRUE) 12 meanlogs_with<-svyby(~log(enroll),~stype,svymean, design=rclus1,covmat=TRUE,return.replicates=TRUE) 18 r<- attr(meanlogs_with, "replicates") globalVar 19 vr_with<-vcov(rclus1,exp(r[,1]-r[,2]))
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/dports/science/py-obspy/obspy-1.2.2/obspy/signal/ |
H A D | polarization.py | 65 covmat = np.zeros([3, 3]) 75 covmat[0][1] = covmat[1][0] = np.cov(datax[i, :], datay[i, :], 77 covmat[0][2] = covmat[2][0] = np.cov(datax[i, :], dataz[i, :], 80 covmat[1][2] = covmat[2][1] = np.cov(dataz[i, :], datay[i, :], 151 covmat = np.cov(x) 152 eigvec, eigenval, v = np.linalg.svd(covmat) 244 covmat = np.zeros([3, 3], dtype=np.complex128) 282 covmat = np.cov(xx) 283 eigvec, eigenval, v = np.linalg.svd(covmat) 361 r = np.sqrt(n ** 2 + e ** 2) [all …]
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/dports/math/R-cran-survey/survey/R/ |
H A D | surveyby.R | 84 if (covmat || return.replicates) { 95 if ((covmat && inherits(design, "svyrep.design")) || return.replicates) { 191 if(covmat) 258 drop.empty.groups=TRUE, covmat=FALSE, influence=covmat, na.rm.by=FALSE, argument 330 if (covmat||influence ) { 331 r<-FUN(data, functionVar 335 r<-FUN(data, 339 attr(r,"index")<-idx 340 r 343 if (covmat || influence) { [all …]
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H A D | surveyrep.R | 670 r <- r & !is.na(r) 1444 if (covmat){ 1469 covmat<-object$vcov functionVar 1470 if (is.null(covmat)){ 1475 dimnames(covmat)<-list(nms,nms) 1476 covmat 1488 r 1744 covmat<-vcov(object) functionVar 1746 var.cf <- diag(covmat) 1771 cov.scaled = covmat)) [all …]
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H A D | multivariate.R | 9 f<-factanal(covmat=v, factors=factors, n.obs=n,...) 45 r <- list(sdev = s$d, rotation = s$v, center = if (is.null(cen)) FALSE else cen, list 47 r$weights<-w/mean(w) 50 r$x <- (x %*% s$v)/sqrt(r$weights) 52 r$naa<-naa 53 r$design<-design 54 class(r) <- c("svyprcomp","prcomp") 55 r
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H A D | survey.R | 317 r <- r & !is.na(r) 318 x<-x[r,] 797 for(r in x$ratios) { functionVar 798 print(r) 1228 r 1249 covmat<-vcov(object) functionVar 1250 dimnames(covmat) <- list(names(coef.p), names(coef.p)) 1251 var.cf <- diag(covmat) 1277 cov.scaled = covmat)) 1279 dd <- sqrt(diag(covmat)) [all …]
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/dports/finance/R-cran-tseries/tseries/R/ |
H A D | finance.R | 38 rf = 0.0, reslow = NULL, reshigh = NULL, covmat = cov(x), ...) argument 45 if(!is.matrix(covmat)) { 48 if((dim(covmat)[1] !=k) || (dim(covmat)[2] !=k)) { 51 Dmat <- covmat 206 function(x, r = 0, scale = sqrt(250)) argument 216 return(scale * (mean(y)-r)/sd(y))
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/dports/math/R-cran-robustbase/robustbase/R/ |
H A D | glmrob.R | 136 covmat <- object$cov functionVar 137 s.err <- sqrt(diag(covmat)) 151 cov.scaled = covmat)) 153 ans$correlation <- cov2cor(covmat) 265 r <- object$residuals functionVar 276 y <- mu + r * mu.eta(eta) 285 working = r, 287 partial = r
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/dports/math/R-cran-psych/psych/man/ |
H A D | factor.fit.Rd | 7 factor.fit(r, f) 11 \item{r}{a correlation matrix } 26 fa4 <- factanal(x,4,covmat=Harman74.cor$cov) 29 fa3 <- factanal(x,3,covmat=Harman74.cor$cov)
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H A D | factor2cluster.Rd | 22 \references{ \url{http://personality-project.org/r/r.vss.html} } 33 f <- factanal(x,4,covmat=Harman74.cor$cov)
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H A D | factor.congruence.Rd | 34 …uction to Psychometric Theory with applications in R (\url{http://personality-project.org/r/book/}) 43 #fa <- factanal(x,4,covmat=Harman74.cor$cov)
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H A D | fa.Rd | 21 factor.minres(r, nfactors=1, residuals = FALSE, rotate = "varimax",n.obs = NA, 24 factor.wls(r,nfactors=1,residuals=FALSE,rotate="varimax",n.obs = NA, 29 …\item{r}{A correlation matrix or a raw data matrix. If raw data, the correlation matrix will be fo… 110 …ce the correlation matrix. This is just \eqn{\frac{\Sigma r_{ij}^2 - \Sigma r^{*2}_{ij} }{\Sigma r… 111 }{(sum(r^2ij - sum(r*^2ij))/sum(r^2ij} (See \code{\link{VSS}}, \code{\link{ICLUST}}, and \code{\li… 138 \item{r.scores}{The correlations of the factor score estimates, if they were to be found.} 157 …lications in R. Springer. Working draft available at \url{http://personality-project.org/r/book/} 177 mle <- factanal(covmat=Harman74.cor$cov,factors=4) 184 mle <- factanal(factors=4,covmat=Harman74.cor$cov,rotation="none") 195 mle2 <- factanal(covmat=Thurstone.33,factors=2,rotation="none") [all …]
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H A D | VSS.Rd | 24 The most important of these is if using a correlation matrix is covmat= xx} 54 …nal correlations: VSS = 1 -sumsquares(r*)/sumsquares(r) where R* is the residual matrix R* = R - … 82 \references{ \url{http://personality-project.org/r/vss.html}, 83 … in R (in prep) Springer. Draft chapters available at \url{http://personality-project.org/r/book/}
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/dports/math/R-cran-geepack/geepack/R/ |
H A D | geeglm.R | 323 covmat <- 330 value$cov.scaled <- value$cov.unscaled <- covmat 332 mean.sum <- data.frame(estimate = object$geese$beta, std.err=sqrt(diag(covmat))) 464 r <- object$residuals functionVar 476 working = r, 478 partial = r)
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/dports/math/apache-commons-math/commons-math3-3.6.1-src/src/main/java/org/apache/commons/math3/stat/regression/ |
H A D | MillerUpdatingRegression.java | 269 r[nextr] = smartAdd(di * r[nextr], (_w * xi) * xk) / dpi; in include() 504 final double[] covmat = new double[nreq * (nreq + 1) / 2]; in cov() local 505 Arrays.fill(covmat, Double.NaN); in cov() 528 covmat[ (col + 1) * col / 2 + row] = total * var; in cov() 536 return covmat; in cov() 633 sumxx += d[row] * r[pos] * r[pos]; in getPartialCorrelations() 657 work[col2 + wrk_off] += d[row] * r[pos1] * r[pos2]; in getPartialCorrelations() 741 r[m1] = r[m2]; in vmove() 771 r[m1] = cbar * r[m2] + sbar * Y; in vmove() 772 r[m2] = Y - X * r[m2]; in vmove() [all …]
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/dports/audio/flite/flite-2.1-release/src/cg/ |
H A D | cst_mlpg.c | 398 pst->r = dcalloc(T, 0); /* [T] */ in InitPStreamChol() 458 pst->r[i] = pst->mseq[i][m]; in calc_R_and_r() 468 pst->r[i] += pst->dw.coef[j][-k] * pst->mseq[n][l]; in calc_R_and_r() 520 pst->g[0] = pst->r[0] / pst->R[0][0]; in Choleski_forward() 527 pst->g[t] = (pst->r[t] - hold) / pst->R[t][0]; in Choleski_forward() 666 pst->g[i] = pst->r[i] - pst->c[i][m] * pst->R[i][0]; 715 clsnum = covmat->row; in xget_detvec_diamat2inv() 716 dim = covmat->col; in xget_detvec_diamat2inv() 721 det *= covmat->data[i][j]; in xget_detvec_diamat2inv() 723 covmat->data[i][j] = 1.0 / covmat->data[i][j]; in xget_detvec_diamat2inv() [all …]
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/dports/audio/festival/festival/src/modules/clustergen/ |
H A D | simple_mlpg.cc | 451 pst->r = dcalloc(T, 0); // [T] in InitPStreamChol() 511 pst->r[i] = pst->mseq[i][m]; in calc_R_and_r() 521 pst->r[i] += pst->dw.coef[j][-k] * pst->mseq[n][l]; in calc_R_and_r() 573 pst->g[0] = pst->r[0] / pst->R[0][0]; in Choleski_forward() 580 pst->g[t] = (pst->r[t] - hold) / pst->R[t][0]; in Choleski_forward() 720 pst->g[i] = pst->r[i] - pst->c[i][m] * pst->R[i][0]; 762 clsnum = covmat->row; in xget_detvec_diamat2inv() 763 dim = covmat->col; in xget_detvec_diamat2inv() 768 det *= covmat->data[i][j]; in xget_detvec_diamat2inv() 770 covmat->data[i][j] = 1.0 / covmat->data[i][j]; in xget_detvec_diamat2inv() [all …]
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/dports/math/R/R-4.1.2/src/library/stats/R/ |
H A D | glm.R | 460 r <- fit$residuals functionVar 506 y=r, 598 r <- m1$residuals functionVar 604 y=r, 680 covmat <- dispersion*covmat.unscaled functionVar 681 var.cf <- diag(covmat) 709 covmat.unscaled <- covmat <- matrix(, 0L, 0L) 725 cov.scaled = covmat)) 827 r <- object$residuals functionVar 843 working = r, [all …]
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/dports/math/libRmath/R-4.1.1/src/library/stats/R/ |
H A D | glm.R | 460 r <- fit$residuals functionVar 506 y=r, 598 r <- m1$residuals functionVar 604 y=r, 680 covmat <- dispersion*covmat.unscaled functionVar 681 var.cf <- diag(covmat) 709 covmat.unscaled <- covmat <- matrix(, 0L, 0L) 725 cov.scaled = covmat)) 827 r <- object$residuals functionVar 843 working = r, [all …]
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/dports/math/R-cran-car/car/R/ |
H A D | S.R | 103 r <- z$residuals functionVar 104 n <- length(r) 111 r <- sqrt(w) * r 117 ans$residuals <- r 140 r <- z$residuals 147 rss <- sum(r^2) 156 r <- sqrt(w) * r 173 ans$residuals <- r 345 covmat <- if(is.matrix(vcov.)) vcov. else functionVar 348 var.cf <- diag(covmat) [all …]
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/dports/misc/elki/elki-release0.7.1-1166-gfb1fffdf3/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/scatterplot/cluster/ |
H A D | EMClusterVisualization.java | 225 double[][] covmat = model.getCovarianceMatrix(); in fullRedraw() local 230 EigenvalueDecomposition evd = new EigenvalueDecomposition(covmat); in fullRedraw() 393 double[] r = pc[k]; in makeHullComplex() local 394 double[] ppqpr = timesEquals(plus(ppq, r), MathUtil.SQRTTHIRD); in makeHullComplex() 395 double[] pmqpr = timesEquals(plus(pmq, r), MathUtil.SQRTTHIRD); in makeHullComplex() 396 double[] ppqmr = timesEquals(minus(ppq, r), MathUtil.SQRTTHIRD); in makeHullComplex() 397 double[] pmqmr = timesEquals(minus(pmq, r), MathUtil.SQRTTHIRD); in makeHullComplex()
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/dports/science/py-scipy/scipy-1.7.1/scipy/stats/ |
H A D | mstats_basic.py | 267 for r in repeats[0]: 268 condition = (data == r).filled(False) 720 covmat = ma.empty((m,m), dtype=float) 729 covmat[j,k] = (K[j,k] + 4*(R[:,j]*R[:,k]).sum() - 732 covmat[k,j] = covmat[j,k] 736 var_szn = covmat.diagonal() 740 z_tot_dep = msign(S_tot) * (abs(S_tot)-1) / ma.sqrt(covmat.sum()) 816 r""" 859 r""" 915 r"""
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/dports/math/R-cran-sm/sm/R/ |
H A D | variogram.r | 379 r <- yy functionVar 385 r <- c(r, fn(est)) 391 r <- c(r, fn(mean(dall) + 2 * se.band), fn(mean(dall) - 2 * se.band)) 395 r <- c(r, fn(gamma.hat - 2 * se), fn(gamma.hat + 2 * se)) 396 replace.na(opt, ylim, range(r)) 609 opt$covmat <- V 864 opt$covmat <- V
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/dports/math/R/R-4.1.2/tests/ |
H A D | reg-examples3.Rout.save | 150 Levels: a b c d e f g h i j k l m n o p q r s t u v w x y z 433 > (pc.rob <- princomp(stackloss, covmat = MASS::cov.rob(stackloss))) 435 princomp(x = stackloss, covmat = MASS::cov.rob(stackloss)) 501 r . . . 2
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/dports/math/libRmath/R-4.1.1/tests/ |
H A D | reg-examples3.Rout.save | 150 Levels: a b c d e f g h i j k l m n o p q r s t u v w x y z 433 > (pc.rob <- princomp(stackloss, covmat = MASS::cov.rob(stackloss))) 435 princomp(x = stackloss, covmat = MASS::cov.rob(stackloss)) 501 r . . . 2
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