similar to: p-values from bootstrap - what am I not understanding?

Hello all, In the course of trying to implement the CDF of an InverseGammaDistribution, I have run across the need for an igamma() function. Several others have needed this function but the answers I have found so far are not totally clear to me. I'm writing for three reasons: 1) to present a small error in the docs 2) to clarify the approach we are expected to take 3) to request,for the

I am a novice user of "R" and I'm learning with R version 2.8.1, using WinEdt_1.8.1, under Widows Vista Home Version. ## The test function below, from a vector input, returns vector values: # and it contains an "ifelse"statement TEST<- function(x) { low<- -x^2 up<- x^4 ifelse(x>=0,up,low ) } u<- seq(-1,1,0.5) TEST(u)

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) }

Good afternoon/morning readers. This is the first time I am trying to run some Bayesian computation in R, and am experiencing a few problems. I am working on a Poisson model for cancer rates which has a conjugate Gamma prior. 1) The first question is precisely how I work out the parameters. #Suppose I assign values to theta with *seq()* *theta<-seq(0,1,len=500)* #Then I try out the

We (the lme4 authors) are having a problem with doing a proper deep copy of a reference class object in recent versions of R-devel with the LAZY_DUPLICATE_OK flag in src/main/bind.c enabled. Apologies in advance for any improper terminology. TL;DR Is there an elegant way to force non-lazy/deep copying in our case? Is anyone else using reference classes with a field that is an external pointer?

Hi, Could you please let me know to use a list in a for loop here geneset is a loop.I am trying to match the names of the list with 1st row of the output. result<- list() for(i in 1:length(output) { result[[i]] <- geneset(which(geneset %n% output[,1])) } Kindly help me out -- View this message in context: http://www.nabble.com/For-loop-tp18163665p18163665.html Sent from the R

Hi, It is most probably just my R-ignorance, but I have following problem with using predict(). I train the model using 164 cases and then I try to use it on the data set with 35 cases, but I am getting 164 predictions ? R-code below illustrates in more detail what I am doing. Truly yours, R train = read.csv("train.csv", header = TRUE, row.names = "mol",

Dear all, is there any function to calculate the center of a polygon mass in R? Actually I need to find the best location within polygons to place labels. Thanks for any hint Jens Oehlschl?gel -- COMPUTERBILD 15/03: Premium-e-mail-Dienste im Test\ --------...{{dropped}}

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to

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,

Hello: I'm dealing with an issue currently that I'm not sure the best way to approach. I've got a very large (10G+) dataset that I'm trying to create a histogram for. I don't seem to be able to use hist directly as I can not create 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

Dear R-List users, Can anyone explain exactly the difference between Weights options in lm glm and gls? I try 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:

I've written a simple function to draw a regression line in a plot and annotate the line showing the slope with a label. It works, as I'm using it, when the horizontal variable is 'x', but gives incorrect results otherwise. What's wrong? # simple function to show the slope of a line show.beta <- function(model, x="x", x1, x2, label, col="black", ...)

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

On Thu, Jul 07, 2016 at 06:08:43PM +0100, Richard W.M. Jones wrote: > On Thu, Jul 07, 2016 at 07:00:46PM +0200, Pino Toscano wrote: > > 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

Pervasives is deprecated since Ocaml 4.08 and has been removed in OCaml 5.0. https://github.com/ocaml/ocaml/pull/1605 --- 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 =

Full_Name: Stephen Eglen 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="")

The division part of the following code is not executing - (seq(n-1)*mean(XS)-cumsum(XS[seq(n-1)]))*diff(XS)/((n-1)*var(XS)) Note: Prof Yatracos: Would you please send them one example ? Thanks, Kaushik -----Original Message----- From: ripley@stats.ox.ac.uk [mailto:ripley@stats.ox.ac.uk] Sent: Friday, August 30, 2002 4:27 PM To: Kaushik Bhattacharyya Cc: r-devel@stat.math.ethz.ch;

Hello, I'm new to boostrapping and I'd need some help to understand the error message that pops up when I run my script. I have a data.frame with 73 lines and 21 column. I am running a stepwise regression to find the best model using the R function "step". I apply bootstrapping to obtain model coefficients. This is my script: # "datare80" is the name of the

Hi everyone, i've been trying to make a special plot with ggplot2, but I can't get it to fill the polygon I'd like to see filled so very very much. I want to display the difference or change in the distribution of the modified Rankin Scale between two groups. mRS is a scale for disability or daily activities competence. It looks like this.