similar to: Shade area under curve

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 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

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'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 all, Currently I have the following output > mydensity <- density(x) > print(mydensity) x y Min. : -92.14 Min. :0.000e+00 1st Qu.: 356.66 1st Qu.:5.530e-09 Median : 805.45 Median :4.681e-05 Mean : 805.45 Mean :5.564e-04 3rd Qu.:1254.24 3rd Qu.:3.370e-04 Max. :1703.04 Max. :5.541e-03 How can I access the Max value of

Dear R users, glm.fit() gave me the same AIC's regardless of TRUE or FALSE intercept option. > myX <- as.matrix(1:10) > myY <- 3+5*myX > foo <- glm.fit(x=myX, y=myY, family = gaussian(link = "identity"), intercept=TRUE) > foo$aic [1] 38.94657 > foo <- glm.fit(x=myX, y=myY, family = gaussian(link = "identity"), intercept=FALSE) > foo$aic [1]

Dear all R gurus, I have following syntax: y = c(1:10) chippy <- function(x) { y[5] = x sin(cos(t(y)%*%y)*exp(-t(y)%*%y/2)) } curve(chippy, 1, 20, n=200) But I am getting error while executing : Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ In addition: Warning message: number of items to

Dear R-users, I have two outliers related questions. I. I have a vector consisting of 69 values. mean = 0.00086 SD = 0.02152 The shape of EDA graphics (boxplots, density plots) is heavily distorted due to outliers. How to define the interval for outliers exception? Is <2SD - mean + 2SD> interval a correct approach? Or should I define 95% (or 99%) limit of agreement for data interval,

Hi All, I have a quick question about using plot.Predict now that the rms package uses lattice. I'd like to add tick marks along the regression line, which is given by data=llist(variablename) in the plot call. The ticks show up fine, but I'd like to alter the color. I know the ticks are produced by scat1d, but after spending a fair bit of time going through documentation, it still

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

Hi R list, I like the default ticks that are set up using grid.xaxis() or grid.yaxis() with no arguments. Finding good values for the 'at' argument is usually not a trivial task; the default behavior of these functions seems to work well. The problem with this strategy is that I cannot figure out how to "recover" the positions of these ticks when you do NOT specify the

Dear R users, I have the following data: x <- data.frame( myX = c(1,2,3,4,5,6,7,8,9) ) y <- data.frame( myX = c(1,2,3,4,5,6,7) ) How can I get the difference between data frame x and y? In this case, I want to get values 8 and 9 I know in SQL we can use minus operator, but I have no idea how to do so in R. I tried all.equal, diff, and identical, but they don't give me the actual data

Environment variables set with Sys.putenv() disappear (i.e. become "") after a while, especially after heavy-duty I/O. Example: R> x <- matrix(1., 3000, 3000) R> save(x, file="myx.RData") R> Sys.putenv(HOME="/tmp") R> while (Sys.getenv("HOME") != "") {cat("ok\n"); load("myx.RData")} The loop prints

Hi everybody, here's my problem: i call a C function which calculates a large number of double values and puts them into an array which is passed from R as a parameter in the function (like .C("function", other parameters, result = as.double( c ( 1 : quantity ) ). When the values come back to R in the result array, they are all truncated to their integer value (i.e. I lose the

Hi, I have a cloud of randomly distributed points in 2-dimensional space and want to set up a grid, with a given grid-cell size, that minimizes the distance between my points and the grid nodes. Does anyone know of an R function or toolbox that somehow addresses this problem? This is a problem of optimizing the location of the grid, not a problem of deciding what should be the grid-cell size,

Hello, I have defined a new class > setClass("myclass", representation(min = "numeric", max = "numeric")) and want to write accessor functions, so that for > foo = new("myclass", min = 0, max = 1) > min(foo) # prints 0 > max(foo) # prints 1 At first i created a generic function for "min" > setGeneric("min",

Hello, I tried to call an external function of R from the following code in C++: void prodgdot(double *x, double *y, int *n, double *output) { int i; *output=0; for (i=0;i<*n;i++) { *output+=x[i]*y[i]; } } I compiled it using from my working directory in linux terminal and I think it's ok: giba at giba-desktop:~/mysrc/meus_testes_iniciais$ R CMD SHLIB

I am new to R so I apologize if my question is trivial. I have not been able to figure out whether what I want to do is even possible. I have a data frame of stock ticker symbols which I store into R space from a txt file as follows: tickers <- read.csv("stocks.txt", header=FALSE, sep=",") tickers <- tickers[1] / the tickers are stored in the first column >

This question concerns rpart's facility for user-defined functions that accomplish splitting. I was interested in modifying the code so that in each terminal node, a linear regression is fit to the data. It seems that from the allowable inputs in the user-defined functions, that this may not be possible, since they have the form: function(y, wt, parms) (in the case of the