similar to: lattice / pdf bug ?

Hello all, Please consider the following library(lattice) Colors. <-rep(brewer.pal(7, "Dark2"),2) color <- 1 Data.X.. <- data.frame(UnitArea = c(rnorm(1000), rnorm(1000)), Type = c(rep("Base",1000),rep("Log",1000))) histogram( ~ UnitArea | Type, data = Data.X.., xlab = "Unit Area", type = "density", panel =

Dear users, I would like to plot several histograms superimposed on the same panel with different colors, with superimposed polygons appearing with transparency effects. I also want estimated densities to appear on the same plot. For several reasons, including that I like it, I want to use the lattice package. I have several questions regarding the use of the 'histogram' function with a

Hi R users, I would like to know why these following curve densities don't appear correctly on the histograms. Thank you for your help library(lattice) library(grid) resp <- rnorm(2000) group <- sample(c("G1", "G2", "G3", "G4"), replace = TRUE, size = 1000) histogram(~ resp | group, col="steelblue", panel = function(x, ...){ std

I would like to add some vertical lines to a lattice plot of histograms. What I am after is a lattice version of abline(v = 1234). The lattice histogram plot is just: histogram( ~ LTSE | approach, data = arrivals) Can anyone point me in the right direction for this? David Scott _________________________________________________________________ David Scott Department of Statistics The

I am interested in plotting histograms for the following data Isoform Tumor_65_198 Tumor_50_192 Tumor_80_167 Tumor_80_204 Tumor_95_197 Tumor_70_189 Tumor_90_202 Tumor_40_177 Tumor_60_21 Tumor_70_174 Tumor_70_147 Tumor_50_5 ABCC4-2007 1 1 1 6 1 9 10 1 2 0 10 1 ABCC4-2008 5 8 7 5 3 10 5 5 7 3 10 3 ABCC4-2009 0 0 0 0 0 0 0 0 0 0 0 0 ABCC4-2010

I'm an R-beginner and have found the function 'panel.mathdensity' in the full manual. R can't find the function and under 'Description' in the manual it says that they "are available in Trellis". What is it and where can I find the function? Regards, M?rten M?rten Bjellerup Doctoral Student in Economics School of Management and Economics V?xj? University

I am using Version 1.3.0 (2001-06-22) on Windows/2000. Had loaded the 'lattice' and 'grid' libraries and was trying the example on densityplot: data(singer) densityplot( ~ height | voice.part, data = singer, layout = c(2, 4), xlab = "Height (inches)", bw = 5) ## Using a predefined panel function to fit a normal distribution

Hello, I have multiple data files. Each file contains a single column and 1.5 million rows. I want to create normalized pdfs (area under curve is 1) and histograms to compare with one another. Could anybody suggest if there exists an easy way or built in function in R. At present I am using Origin and Excel together to do this. A single file needs 10 minutes and I have a total of 929 files! So

Hello, I am new to R exploratory data analysis and plotting. Is anyone aware of a way to overlay a set of conditional histograms with conditional PDFs? Below, I generate a lattice plot of precipitation histograms based on different months and stations, given a subset of the dataset: histogram(~ data | month * station, data = sta.stack[sta.stack[,"type"]=="precip" &

. I am looking for a histogram or box plot with the adding normal distribution curve I think that must be possible, but I am not able to find out how to do. Regards Knut

Dear list, has anyone written a package/function in R for computing a point- biserial resp. biserial correlation? Thanks in advance Bernd

Ah, with R 3.5.0 or R 3.4.2, but not with R 3.3.1, 'eval' inside 'for' makes compiled version behave like non-compiled version. options(error = expression(NULL)) library(compiler) enableJIT(0) f <- function(x) for (i in 1) {x; eval(expression(i))} f(is.numeric(y)) # Error: object 'y' not found fc <- cmpfun(f) fc(is.numeric(y)) # Error: object 'y' not found

My points: - The 'withCallingHandlers' construct that is used in current 'stopifnot' code has no effect. Without it, the warning message is the same. The overridden warning is not raised. The original warning stays. - Overriding call in error and warning to 'cl.i' doesn't always give better outcome. The original call may be "narrower" than 'cl.i'. I

I believe the performance of isUnsorted() in sort.c could be improved by calling REAL() once (outside of the for loop), rather than calling it twice inside the loop. As an aside, it is implemented in the faster way in doSort() (sort.c line 401). The example below shows the performance improvement for a vectors of double of moving REAL() outside the for loop. # example as implemented in

>From https://github.com/HenrikBengtsson/Wishlist-for-R/issues/70 : ... and follow up note from 2018-03-15: Ouch... in R-devel, stopifnot() has become yet 4-5 times slower; ... which is due to a complete rewrite using tryCatch() and withCallingHandlers(). >From https://stat.ethz.ch/pipermail/r-devel/2017-May/074256.html , it seems that 'tryCatch' was used to avoid the following

Here is a patch to function 'stopifnot' that adds 'evaluated' argument and makes 'exprs' argument in 'stopifnot' like 'exprs' argument in 'withAutoprint'. --- stop.R 2019-05-30 14:01:15.282197286 +0000 +++ stop_new.R 2019-05-30 14:01:51.372187466 +0000 @@ -31,7 +31,7 @@ .Internal(stop(call., .makeMessage(..., domain = domain))) }

>>>>> Herv? Pag?s <hpages at fredhutch.org> >>>>> on Mon, 15 May 2017 16:54:46 -0700 writes: > Hi, > On 05/15/2017 10:41 AM, luke-tierney at uiowa.edu wrote: >> This is getting pretty convoluted. >> >> The current behavior is consistent with the description at the top of >> the help page -- it does not

I think Herv?'s idea was just that if switch can evaluate arguments selectively, so can stopifnot(). But switch() is .Primitive, so does it from C. I think it is almost a no-brainer to implement a sequential stopifnot if dropping to C code is allowed. In R it gets trickier, but how about this: Stopifnot <- function(...) { n <- length(match.call()) - 1 for (i in 1:n) { nm

If an expression is passed to stopifnot() which contains missing values, then the resulting error message is somewhat baffling until you are used to it, e.g. > x <- y <- rep(TRUE, 10) > y[7] <- NA > stopifnot(x, y) Error in if (!(is.logical(r <- eval(ll[[i]])) && all(r))) stop(paste(deparse(mc[[i + : missing value where TRUE/FALSE needed A minor change to

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")