/dports/math/R-cran-gss/gss/R/ |
H A D | cdsscden.R | 8 ynames <- NULL functionVar 9 for (i in object$ynames) 10 if (all(i!=colnames(cond))) ynames <- c(ynames,i) 11 if (any(length(ynames)==c(0,length(object$ynames)))) 15 colnames(y) <- ynames 25 for (ylab in ynames) { 91 ynames <- NULL functionVar 92 for (i in object$ynames) if (all(i!=colnames(cond))) ynames <- c(ynames,i) 107 colnames(y.wk) <- ynames 151 ynames <- NULL functionVar [all …]
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H A D | dsscden.R | 7 if (length(object$ynames)==1&is.vector(y)) { 9 colnames(y) <- object$ynames 11 if (!all(sort(object$ynames)==sort(colnames(y)))) 37 mn <- min(ydomain[[object$ynames]]) 38 mx <- max(ydomain[[object$ynames]]) 47 colnames(y.wk) <- object$ynames 91 mn <- min(ydomain[[object$ynames]]) 92 mx <- max(ydomain[[object$ynames]]) 101 colnames(y.wk) <- object$ynames 141 if (!all(sort(object$ynames)==sort(colnames(y)))) [all …]
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H A D | sscden1.R | 41 xnames <- vars[!(vars%in%ynames)] 45 for (ylab in ynames) { 101 if (length(ynames)>1) { 102 for (ylab in ynames[-1]) { 107 colnames(qd.pt) <- ynames 108 qd.wt <- as.vector(table(mf[,rev(ynames)])) 156 for (ylab in ynames) { 167 env <- list(ynames=ynames,ydomain=ydomain,qd.pt=quad$pt,qd.wt=quad$wt,rho=rho) globalVar 170 for (ylab in env$ynames) { 221 y.list <- ynames[ynames%in%vlist] [all …]
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H A D | predict.ssllrm.R | 13 if (!all(sort(object$ynames)==sort(colnames(y)))) 22 if (!sum(duplicated(rbind(qd.pt,y[i,object$ynames,drop=FALSE])))) 26 if (sum(duplicated(rbind(qd.pt[j,],y[i,object$ynames])))) y.id <- c(y.id,j) 50 y.list <- object$ynames[object$ynames%in%vlist] 105 for (ylab in object$ynames) {
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/graphics/ |
H A D | correlation.py | 15 def plot_corr(dcorr, xnames=None, ynames=None, title=None, normcolor=False, argument 73 if ynames is None: 74 ynames = xnames 90 if isinstance(ynames, list) and len(ynames) == 0: 92 elif ynames is not None: 95 ax.set_yticklabels(ynames[::-1], fontsize='small', 126 ynames=None, fig=None, cmap='RdYlBu_r'): argument 185 if ynames is None: 186 ynames = xnames 212 _ynames = ynames if (i+1) % ncols == 1 else [] [all …]
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/dports/devel/R-cran-gmodels/gmodels/R/ |
H A D | estimable.mlm.R | 9 ynames <- colnames(coef) functionVar 10 if (is.null(ynames)) { 13 ynames <- as.character(lhs)[-1] 14 else ynames <- paste("Y", seq(ny), sep = "") 17 names(value) <- paste("Response", ynames) 25 obj$call$formula[[2]] <- obj$terms[[2]] <- as.name(ynames[i])
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/dports/math/R-cran-KFAS/KFAS/R/ |
H A D | SSMtrend.R | 3 SSMtrend <- function(degree = 1, Q, type, index, a1, P1, P1inf, n = 1, state_names = NULL, ynames) { argument 7 if (!missing(ynames) && !is.null(ynames)) { 8 ynames <- paste0(".", ynames) 9 } else ynames <- "" 91 "1" = paste0("level", ynames), 92 "2" = paste0(c("level", "slope"), rep(ynames, each = degree)), 93 paste0("trend", rep(1:degree), rep(ynames, each = degree)))
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H A D | SSMarima.R | 5 index, n = 1, state_names = NULL, ynames) { argument 13 if (!missing(ynames) && !is.null(ynames)) { 14 ynames <- paste0(".", ynames) 15 } else ynames <- "" 67 state_names <- paste0(rep(paste0("arima", 1:m1), p), rep(ynames, each = m1))
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H A D | SSMcycle.R | 3 …- function(period, Q, type, index, a1, P1, P1inf, damping = 1, n = 1, state_names = NULL, ynames) { argument 7 if (!missing(ynames) && !is.null(ynames)) { 8 ynames <- paste0(".", ynames) 9 } else ynames <- "" 36 state_names <- paste0(c("cycle", "cycle*"), rep(ynames, each = 2))
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H A D | SSMseasonal.R | 4 type, index, a1, P1, P1inf, n = 1, state_names = NULL, ynames, harmonics) { argument 11 if (!missing(ynames) && !is.null(ynames)) { 12 ynames <- paste0(".", ynames) 13 } else ynames <- "" 31 rep(ynames, each = period - 1)) 37 1)), rep(1:floor(period/2), each = 2, length.out = (period - 1)), rep(ynames,
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H A D | SSMregression.R | 4 P1inf, n = 1, remove.intercept = TRUE, state_names = NULL, ynames) { argument 11 if (!missing(ynames) && !is.null(ynames)) { 12 ynames <- paste0(".", ynames) 13 } else ynames <- "" 58 state_names <- paste0(rep(Xnames, times = (p - 1) * (type == 1) + 1), rep(ynames, 113 state_names <- c(state_names, paste0(colnames(X[[i]]), ynames[i]))
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/dports/math/py-statsmodels/statsmodels-0.13.1/statsmodels/base/ |
H A D | data.py | 330 def ynames(self): member in ModelData 332 ynames = self._get_names(endog) 333 if not ynames: 336 if len(ynames) == 1: 337 return ynames[0] 339 return list(ynames) 569 return DataFrame(result, index=self.ynames, columns=self.ynames) 583 out.columns = self.ynames 598 columns=self.ynames) 616 ynames = ['y'] [all …]
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/dports/finance/R-cran-vars/vars/R/ |
H A D | summary.varest.R | 3 ynames <- colnames(object$y) functionVar 6 names <- ynames 10 if (!(all(names %in% ynames))) { 12 names <- ynames[1]
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H A D | plot.varstabil.R | 6 ynames <- x$names functionVar 8 names <- ynames 11 if (!(all(names %in% ynames))) { 13 names <- ynames[1]
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H A D | predict.varest.R | 8 ynames <- colnames(object$y) functionVar 77 colnames(yse) <- paste(ci, "of", ynames) 88 colnames(forecast) <- paste(ynames, ".fcst", sep="") 90 colnames(lower) <- paste(ynames, ".lower", sep="") 92 colnames(upper) <- paste(ynames, ".upper", sep="") 98 names(forecasts) <- ynames
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H A D | predict.vec2var.R | 8 ynames <- colnames(object$y) functionVar 59 colnames(yse) <- paste(ci, "of", ynames) 70 colnames(forecast) <- paste(ynames, ".fcst", sep="") 72 colnames(lower) <- paste(ynames, ".lower", sep="") 74 colnames(upper) <- paste(ynames, ".upper", sep="") 80 names(forecasts) <- ynames
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H A D | plot.varfevd.R | 5 ynames <- names(x) functionVar 8 names <- ynames 11 if (!(all(names %in% ynames))) { 13 names <- ynames[1] 23 ifelse(is.null(legend), legend <- ynames, legend <- legend)
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H A D | fevd.svarest.R | 9 ynames <- colnames(x$var$datamat[, 1 : K]) functionVar 28 colnames(result[[i]]) <- ynames 30 names(result) <- ynames
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H A D | fevd.varest.R | 9 ynames <- colnames(x$datamat[, 1 : K]) functionVar 32 colnames(result[[i]]) <- ynames 34 names(result) <- ynames
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H A D | fevd.vec2var.R | 9 ynames <- colnames(x$datamat[, 1 : K]) functionVar 32 colnames(result[[i]]) <- ynames 34 names(result) <- ynames
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H A D | fevd.svecest.R | 11 ynames <- colnames(varlevel$datamat[, 1 : K]) functionVar 30 colnames(result[[i]]) <- ynames 32 names(result) <- ynames
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H A D | fanchart.R | 28 ynames <- colnames(endog) functionVar 30 names <- ynames 33 if (!(all(names %in% ynames))) { 35 names <- ynames[1]
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H A D | plot.varprd.R | 4 ynames <- colnames(x$endog) functionVar 9 names <- ynames 12 if(!(all(names %in% ynames))){ 14 names <- ynames[1]
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/dports/math/R-cran-raster/raster/R/ |
H A D | coverPolygons.R | 69 ynames <- colnames(y@data) functionVar 71 ynames <-NULL 73 if (is.null(xnames) & !is.null(ynames)) { 77 xnames <- ynames 80 yinx <- which(ynames %in% xnames)
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H A D | intersect_sp.R | 48 colnames(y@data) <- ynames <- nms[(ncol(x@data)+1):length(nms)] functionVar 55 ynames <- colnames(dat) 83 dat[rows, ynames] <- y@data[idsy, ] 183 colnames(y@data) <- ynames <- nms[(ncol(x@data)+1):length(nms)] functionVar 190 ynames <- colnames(dat) 218 dat[rows, ynames] <- y@data[idsy, ] 288 ynames <- nms[(ncol(x@data)+1):length(nms)] functionVar 292 colnames(d) <- c(xnames, ynames)
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