search for: ys

Dear R-users Idea: Plot a dnorm line using specific mean/sd to complete a histogram (skewed). xs:range of y-values, ys: dnorm function Problem: I expected to multiply the ys function with the sample size (n=250-300). I was wondering about a factor between 12'000 and 30'000 to match the size of the dnorm line with the specific histogram. Thanks Sibylle hist(Biotree[Ld,]$Height2008, main="Larix decidu...

Hi, a have some code like myfunc <- function(x) { ...; return c(a,b) } ys <- sapply(0:100,myfunc) so I get something like c(c(a1,b1),c(a2,b2),...) But now I need the "as" and "bs" in one vector as <- apply(ys, function(c(a,b)) a) bs <- apply(ys, function(c(a,b)) b) Can you help me with the correct syntax, instead of my pseudo code? thx C...

Hello. I am new R user, so this question is probably quite stupid, but for the life of me I cannot figure out how to get predications using multivariate linear regression analysis. Single variable predictions work fine. I am trying the following: -- Known y's for known x's1 and x's2 ys <- c(133890, 135000, 135790, 137300, 138130, 139100, 139900, 141120, 141890, 143230, 144000, 145290) xs1 <- c(1:12) xs2 <- c(22, 24.5, 27, 33, 36.8, 40, 44, 57, 59, 6...

Here's some code to make lissajous dance. I've attached a small sample GIF. Cheers, Rob Steele robsteele at yahoo dot com plot.lissajous = function(omega.x, omega.y, delta = 0, num.thetas = 200) { thetas = seq(0, 2 * pi, length = num.thetas) xs = sin(omega.x * thetas + delta) ys = cos(omega.y * thetas) plot(xs, ys, type = 'l', lwd = 3, ann = FALSE, axes = FALSE) } ## Show one. par(mar = c(2, 2, 2, 2)) plot.lissajous(4, 3) ## Animate it. while (TRUE) { for (delta in seq(0, 2 * pi, length = 120)) { plot.lissajous(4, 3, delta) Sys.sleep(1 / 30)...

...reate an R vector of size greater than 2.2G. I considered condensing the data previous to loading it into R and just plotting the frequencies as a barplot; unfortunately, barplot does not support plotting the values according to a set of x-axis positions. What I have is something similar to: ys <- c(12,3,7,22,10) xs <- c(1,30,35,39,60) and I'd like the bars (ys) to appear at the positions described by xs. I can get this to work on smaller sets by filling zero values in for missing ys for the entire range of xs but in my case this would again create a vector too large for R....

..."X" = x) > my_df Z Y X 1 1 4 Yes 2 2 1 No 3 3 2 Perhaps 4 4 3 Yes 5 5 4 No 6 6 5 No 7 7 1 Yes 8 8 4 Perhaps 9 9 4 Yes 10 10 2 Perhaps > I am now looking for a table that will give me this: Yes 3 # Yes has these ys: 4,3,1,4, two are the same, ergo 3 No 3 # No has these ys: 1,4,5 Perhaps 2 # Perhaps has these ys: 2,4,2 My dataframe has lots of other colums too, but I only want this information out. Thankyou for your help! Karin -- Karin Lagesen, PhD student karin.lagesen at medisin.uio....

.../www.mathworks.com/matlabcentral/fileexchange/22643-circle-fit-pratt-method/content/CircleFitByPratt.m, based on: *V. Pratt, "Direct least-squares fitting of algebraic surfaces", Computer Graphics, Vol. 21, pages 145-152 (1987)* I am looking for new methods to compare and improve my analysis because the error increase with decreasing of points used in the functions. Thanks for all suggestions Gianni Here the funtions with example # fitCircle, returns: # xf,yf = centre of the fitted circle # Rf = radius of the fitted circle # Cf = circumference of the fitted circle # Af = Area of...

...mlstdutils/std_utils.ml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/mlstdutils/std_utils.ml b/mlstdutils/std_utils.ml index 0d2fa22..86b21a7 100644 --- a/mlstdutils/std_utils.ml +++ b/mlstdutils/std_utils.ml @@ -341,12 +341,12 @@ module List = struct | x::xs, y::ys, z::zs -> (x, y, z) :: combine3 xs ys zs | _ -> invalid_arg "combine3" - let rec assoc_lbl ?(cmp = Pervasives.compare) ~default x = function + let rec assoc_lbl ?(cmp = Stdlib.compare) ~default x = function | [] -> default | (y, y') :: _ when cmp...

...en the bars would fill in the same colors as the bar segments do. Interestingly, in the example provided by the geom_polygon help page, there is a fill, which leads me to suspect that something with my data frame might be wrong. If I supply a "colour" argument, I get borders, but not always in the color I defined. The attached image has such borders, to make clear what polygons I am talking about. In the final plot I don't desire such borders, only the as of yet unattainable fill. Here's my code: library(ggplot2) library(plyr) # define good looks no_margins <- opts(...

...hat's wrong? # simple function to show the slope of a line show.beta <- function(model, x="x", x1, x2, label, col="black", ...) { abline(model, col=col, lwd=2) # x <- deparse(substitute(x)) # doesn't help xs <- data.frame(x=c(x1, x2, x2)) ys <- predict(model, xs) lines(cbind(xs,ys[c(1,1,2)]), col=col) text(x2, mean(ys[1:2]), label, col=col, ...) } x=rnorm(10) DF <- data.frame(x, y=.25*x+rnorm(10)) # OK with(DF, { plot(y ~ x) mod <- lm(y ~ x) show.beta(mod, "x", -0.5, 0, "b", pos=4...

...the following codes, but the results are different. > lm1 Call: lm(formula = y ~ x) Coefficients: (Intercept) x 0.1183 7.3075 > lm2 Call: lm(formula = y ~ x, weights = W) Coefficients: (Intercept) x 0.04193 7.30660 > lm3 Call: lm(formula = ys ~ Xs - 1) Coefficients: Xs Xsx 0.04193 7.30660 Here ys= y*sqrt(W), Xs<- sqrt(W)*cbind(1,x) So we can see weights here for lm means the scale for X and y. But for glm and gls I try > glm1 Call: glm(formula = y ~ x) Coefficients: (Intercept) x 0.1183 7.3...

...tepAIC. But I don't know how it is interpreted . I could not any find any explanation about it For instance which model is preferable ? What are the critarias to choose beter model I will appreciate if you give me an explanation ? models --------- > lo1.step$anova Stepwise Model Path Analysis of Deviance Table Initial Model: res ~ as.factor(jeo) + as.factor(eg) + as.factor(ys) + as.factor(yy) + as.factor(ak) Final Model: res ~ as.factor(jeo) + as.factor(eg) + as.factor(ys) + as.factor(yy) + as.factor(ak) Step Df Deviance Resid. Df Resid. Dev AIC 1...

...") x.scale <- attr(xr, "scaled:scale") mask <- apply(xr, 2, function(x) any(is.na(x))) xr <- xr[,!mask] # rm NA's model <- lm(yr ~ xr) # fit linear model test <- read.csv("test.csv", header = TRUE, row.names = "mol", comment.char="") ys <- test[,1] xs <- test[,-1] xs <- scale(xs, center = x.center, scale = x.scale) xs <- xs[,!mask] xs <- as.data.frame(xs) pr <- predict(model, as.data.frame(xr)) ps <- predict(model, xs) cat("length(yr) =", length(yr), "; length(pr) =", length(pr),"\n&...

...Version: 1.4 OS: Redhat Linux 7.1 Submission from: (NULL) (128.252.204.36) abline() produces a spurious line in addition to the correct line, at least with the X11 driver. The postscript file generated also has nan values in it, which causes an error under ghostscript. xs <- c(0, 150, 300) ys <- c(75, 40, 23) par(mfrow=c(1,2)) plot(xs,ys, log="") abline(70, -0.25, -.1, untf=F) plot(xs,ys, log="y") abline(70, -0.3, -.1, untf=T) dev.copy2eps(file="abline.ps") -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing...

...ggplot2:::ggname("geom_split_violin", GeomPolygon$draw_panel(newdata, ...)) } }) create_quantile_segment_frame <- function (data, draw_quantiles, split = FALSE, grp = NULL) { dens <- cumsum(data$density)/sum(data$density) ecdf <- stats::approxfun(dens, data$y) ys <- ecdf(draw_quantiles) violin.xminvs <- (stats::approxfun(data$y, data$xminv))(ys) violin.xmaxvs <- (stats::approxfun(data$y, data$xmaxv))(ys) violin.xs <- (stats::approxfun(data$y, data$x))(ys) if (grp %% 2 == 0) { data.frame(x = ggplot2:::interleave(violin.xs, violin.xmax...

...nProblem/gtResultSigma10.jpg. fromTime <- 0 toTime <- 250 by <- 1 ts <- seq(from=fromTime, to=toTime) f1 <- 0.01 f2 <- 0.05 t1 <- 50 t2 <- 80 K <- 15 fMax <- 0.20 nf <- 100 df <- fMax/(nf/2) scale <- 10 ys <- sin(2*pi*f1*ts) + sin(2*pi*f2*ts) ys[t1] <- K ys[t2] <- K plot(x=ts, y=ys, xlab="Time", ylab="Signal", type="b") cgtsinwave <- cgt(input=ys, nvoice=nf, freqstep=df, scale=scale, plot=TRUE) Many thanks, Joaquin -- Joaquin Rapela, PhD S...

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...pdf the 5 plots . So i want plots for const=1:5 which change the undelying data expressed in t1 and t2. I attempt some trials , while, for and now repeat loop now , but didn't getting success . I get only the first plot and the loop hang? Many thanks for help ,Christian. #modeldat and YS are data.frames. special <- function(const,modeldat,YS) { const=const repeat { t1 <- apply(YS,1, function(x) { ifelse(all(is.na(x)) | all(na.omit(x) < 0 ,NA, which( x > const ))}) t1[is.na(t1)] <- 13 t2 <- sapply(t1,function(x) { ifelse(x ==13,0,1)}) modeldat$MONTH &l...

On Thursday 07 July 2016 17:30:03 Richard W.M. Jones wrote: > This adds imperative list manipulation functions inspired by Perl. > The functions are passed list refs which get updated in place. > > This allows us to replace some awkward pure functional code like: > > let xs = ys in > let xs = if foo then xs @ zs else xs in > > with: > > let xs = ref ys in > if foo then append xs zs; > --- TBH I've always found the "shift" and "unshift" naming of Perl functions slightly awkward, but can live with them. (At least the new...

-----Original Message----- From: r-help-request at stat.math.ethz.ch [mailto:r-help-request at stat.math.ethz.ch] Sent: Tuesday, July 01, 2003 3:09 AM To: r-help at stat.math.ethz.ch Subject: R-help Digest, Vol 5, Issue 1 At 18:48 30/06/2003, Martin Wegmann wrote: >hello, > >I want to do a test for spatial correlation. >I tried it with geary.test() but I don't understand the