similar to: Accessing Max/Min Value of Density Function

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.

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

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

Dear People, I have a data set of data x from a probability distribution, and I have a function, mydensity, of the pdf of that distribution. I'm asking for help in superimposing the histogram of x and the plot of mydensity. In the function below, I call truehist and curve, but these are plotted in different figures. I'd like them to be plotted on the same figure, and to use common

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 want to shade the area under the curve of the standard normal density. Specifically color to the left of -2 and on. How might i go about doing this? Thanks -- View this message in context: http://n4.nabble.com/Shade-area-under-curve-tp1586439p1586439.html Sent from the R help mailing list archive at Nabble.com.

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

Dear all, I want to : 1. Estimate a weighted 2D kernel. 2. Paint a heatmap on a ggmap. Here is some reproducible data / code (I got it from the internet) : s_rit <- structure(list(score = c(45, 60, 38, 98, 98, 53, 90, 42, 96, 45, 89, 18, 66, 2, 45, 98, 6, 83, 63, 86, 63, 81, 70, 8, 78, 15, 7, 86, 15, 63, 55, 13, 83, 76, 78, 70, 64, 88, 61, 78, 4, 7, 1, 70, 88, 58, 70, 58, 11, 45, 28, 42,

Un texte encapsul? et encod? dans un jeu de caract?res inconnu a ?t? nettoy?... Nom : non disponible URL : <https://stat.ethz.ch/pipermail/r-help/attachments/20080523/7061f532/attachment.pl>

Hi, I have two histograms created separately using the following code. It creates two separate figures. dat <- read.table(file="GDS1096.modelout", head = FALSE ) __BEGIN__ dat <- read.table(file="GDS1096.modelout", head = FALSE ) hist(dat$V2, main="AIC Freq", xlab = "\# Component", breaks = 36, xlim = c(0,max(dat$V2)), col = "dark red",

Dear People, I am sure I am missing something obvious as usual, but in the following graph I can't plot ylab. Ignoring unimportant details, I am plotting one instance of truehist() and one instance of curve() on the same graph. Truehist() won't let me pass the ylab argument. It gives me the error Error in plot.default(xlim, c(0, ymax), type = "n", xlab = xlab, ylab =

Hi, I have this string, in which I want to extract some of it's element: > x <- "Best-K Gene 11340 211952_at RANBP5 Noc= 3 - 2 LL= -963.669 -965.35" yielding this array [1] "211952_at" "RANBP5" "2" In Perl we would do it this way: __BEGIN__ my @needed =(); my $str = "Best-K Gene 11340 211952_at RANBP5 Noc= 3 - 2 LL= -963.669

Let me start by introducing myself as a biologist with only a little knowledge about programming in matlab and R. In the past I have succesfully created my figures in matlab using the hist3d command, but I have not access to matlab right now and would like to switch to R. I have used the plot command to create a figure of my data and it does almost what I want it to do. My data matrix looks like

Hello, I am a new R user and I am trying to estimate some generalized linear models (glm). I am trying to compare a model with a gaussian distribution and an identity link function, and a poisson model with a log link function. My problem is that while the gaussian model has significantly lower (i.e. "better") AIC (Akaike Information Criterion) most of the coefficients are not

I got the following warning messages when I did a binomial logit regression using glm(): Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, Can some one share your thoughts on how to

Hi all, Hope someone could help me. I am trying to run automatically the conversion of an Rwn file to a tex file. I am using windows 7, and cygwin. I tried to run automatically the Sweave.sh script, in its the most recent version available at R webpage: http://cran.r-project.org/contrib/extra/scripts/Sweave.sh Unfortunately, I got this error message: =========================== Raquel at

In my undertstanding of the problem, the model lme1 <- lme(resp~fact1*fact2, random=~1|subj) should be ok, providing that variances are homogenous both between & within subjects. The function will sort out which factors & interactions are to be compared within subjects, & which between subjects. The problem with df's arises (for lme() in nlme, but not in lme4), when

Hi, I am finding that I get quite different results when I interchange the following "equivalent" lines for sampling from a beta distribution in my r script. The rbeta line is correct judging by the summary statistics of the simulated values, while the qbeta line consistently leads to a higher mean simulated value. simulation <- rbeta(1, alpha, beta) simulation <- qbeta(runif(1),

Dear ExpeRts, Suppose I have a typical psychological experiment that is a within-subjects design with multiple crossed variables and a continuous response variable. Subjects are considered a random effect. So I could model > aov1 <- aov(resp~fact1*fact2+Error(subj/(fact1*fact2)) However, this only holds for orthogonal designs with equal numbers of observation and no missing values.

The message for aov1 was "Estimated effects <may> be unbalanced". The effects are not unbalanced. The design is 'orthogonal'. The problem is that there are not enough degrees of freedom to estimate all those error terms. If you change the model to: aov1 <- aov(RT~fact1*fact2*fact3+Error(sub/(fact1+fact2+fact3)),data=myData) or to aov2 <-