similar to: plotmath question

Greetings: I would like comments on this example and after fixing it up, I need help from someone who has access to insert this in R's help page for plotmath. I uploaded a drawing http://pj.freefaculty.org/R/Normal-2009.pdf that is created by the following code http://pj.freefaculty.org/R/Normal1_2009_plotmathExample.R This will be a good addition to the plotmath help page/example.

Here's another example of my plotmath whipping boy, the Normal distribution. A colleague asks for a Normal plotted above a series of axes that represent various other distributions (T, etc). I want to use vectors of equations in plotmath to do this, but have run into trouble. Now I've isolated the problem down to a relatively small piece of working example code (below). If you would

I've been testing plotmath. But I'm getting some funny output one one computer. The problem is that characters are 'jumbled' and overstrike when symbols are introduced. Sample code: mu <- 440.0 sigma <- 12.5 myx <- seq( mu - 4*sigma, mu+ 4*sigma, length.out=500) myDensity <- dnorm(myx,mean=mu,sd=sigma) # Here's one way to retrieve the values of mu and sigma and

I'm using R-2.6.2 on Fedora Linux 9. I've been experimenting with plotmath. I wish it were easier to combine expressions in plotmath with values from the R program itself. There are two parameters in the following example, the mean "mymean" and standard deviation "mystd". I am able to use bquote to write elements into the graph title like mu = mymean and R will

Suppose I have a plot plot(1:10, pch = "") And I want some text to indicate a Normal distrubition. I could do this: text(5, 6, substitute(X~~~~N(mu, sigma^2)), adj = 0) text(5.35, 6, "~", adj = 0) But that's clumsy, and depending on your plotting device, might not even look sensible. I'd prefer to be able to do it more directly and simply the way these do: text(5,

This is a followup to a recent post on using atop() to obtain multiline expressions. My reading of the plotmath docs makes it clear that issuing (in base graphics) the specification par(cex = 2) doubles symbols and regular text in subsequent plotmath expressions. However, it is unclear to me what specifying cex _within_ the annotation function using plotmath should do, and the following seems

I hope to use the plotmath facility to print titles that mix math and values of R variables. The help for "plotmath" has an example, which after repeated reading, I find baffling. Likewise, I have read the help file for "substitute" (wqhich seems to be needed) without ever understanding what it does, other than being used in some magic incantations. I would like to do

I believe this may be more related to analysis than it is to R, per se. Suppose I have the following function that I wish to integrate: ff <- function(x) pnorm((x - m)/sigma) * dnorm(x, observed, sigma) Then, given the parameters: mu <- 300 sigma <- 50 m <- 250 target <- 200 sigma_i <- 50 I can use the function integrate as: > integrate(ff, lower= -Inf, upper=target)

Hi all, Is there any other packages to do numerical integration other than the default 'integrate'? Basically, I am integrating: integrate(function(x) dnorm(x,mu,sigma)/(1+exp(-x)),-Inf,Inf)$value The integration is ok provided sigma is >0. However, when mu=-1.645074 and sigma=17535.26 It stopped working. On the other hand, Maple gives me a value of 0.5005299403. It is an

Hello! Does someone know how to produce L(y|mu) with plotmath? Some code with unsuccessfull results: plot(dnorm(x = seq(from = -4, to = 4, by = 0.1)), type = "l") ## Not what I want legend(legend = c(expression(L(y:mu))), x = "topright") ## Strange, is this a bug? legend(legend = c(expression(L(y|mu))), x = "top") ## Group produces an error legend(legend =

Hi Folks! Just started using the gamlss package and I tried a simple code example (see below). Why the negative sigma? John > y <- rt(100, df=1)> m1<-fitDist(y, type="realline")Warning messages:1: In MLE(ll3, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma, : possible convergence problem: optim gave code=1 false convergence (8)2: In MLE(ll4, start = list(eta.mu =

Dear friends - I'm on winXP, R 2.71 - I have with some help dveloped this multivariate normal model, which gives very plausible results in WinBUGS even without any initial values specified. However, when I then try to run the same model via the bugs function in R2WinBUGS with inits specified as inits=NULL the program stops in a dead end. So I have tried to make inits for the bugs function

Yes, that looks like a bug and an easily fixable one too. However, I spy another issue: Why do we check the !R_FINITE(x) && mu == x before checking for sd < 0 ? The difference is whether we return ML_NAN; or ML_ERR_return_NAN; but surely negative sd should always be an error? I'd be inclined to do if (sigma < 0) ML_ERR_return_NAN; if(!R_FINITE(sigma)) return R_D__0;

Can someone help me understand the following: > D(expression(dnorm(x, mean)), "mean") [1] 0 > sessionInfo() R version 2.2.1, 2005-12-20, i386-pc-mingw32 attached base packages: [1] "methods" "stats" "graphics" "grDevices" "utils" "datasets" [7] "base" By my computations, this should be

Dear All I am trying to replicate a numerical application (not computed on R) from an article. Using, ks.test() I computed the exact D value shown in the article but the p-values I obtain are quite different from the one shown in the article. The tests are performed on a sample of 37 values (please see "[0] DATA" below) for truncated Exponential, Pareto and truncated LogNormal

Dear list, I am trying to use the 'mvrnorm' function from the MASS package for simulating multivariate Gaussian data with given covariance matrix. The diagonal elements of my covariance matrix should be the same, i.e., all variables have the same marginal variance. Also all correlations between all pair of variables should be identical, but could be any value in [-1,1]. The problem I am

I color some area grey with polygon() (with a red border) and then I want to have the dashed red border in the legend as well. How do I manage it? And I want to mix (latex) expressions with text in my legend. Just execute my lines below and you know want I mean. Or pass by at http://de.wikipedia.org/wiki/Bild:GBM.png to see the picture online. Thomas bm <- function(n=500, from=0, to=1) {

Hi List, I would like to plot multiple curves (parametric density curves) in one plot. For example: # parameters for three normal density curves parms = data.frame(ID=c(1,2,3),mu=c(50,55,60),sigma=c(10,12,15)) # I can easily draw three normal density curves using curve(): curve(dnorm(x,mean=parms$mu[1],sd=parms$sigma[1]),from=0, to=150, ylab="density", col="red")

Here's one possibility, assuming muhat and sigmahat are estimtes of mu and sigma from N iid draws of N(mu, sigma^2): tStat <- abs(x - muhat) / sigmahat pValue <- pt(tStat, df=N, lower=TRUE) I'm not quite sure what df tStat should have (exercise for math stat), but given fairly large N, that should make little difference. Andy > From: Ross Clement > > Hi. I have a

All, I'd like to simulate a vector that is formed from many distinct distributions and avoid a loop if possible. E.g, consider: mu = c(1, 2, 3) sigma = c(1, 2, 3) n = c(10, 10, 10) And we simulate a vector of length 30 that consists of N(mu[i], sigma[i]) distributed data, each of length n[i]. Of course for just three groups we can simply write it out as: DV = c(rnorm(n[1], mu[1],