| /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$ynames) if (all(i!=colnames(cond))) ynames <- c(ynames,i)
107 colnames(y.wk) <- ynames
151 ynames <- NULL functionVar
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| H A D | dsscden.R | 7 if (length(object$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]
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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 []
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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']
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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)
|