similar to: post-hoc comparisons in GAMs (mgcv) with parametric terms

Hello fellow R's, I?ve been learning to use the ggplot2 library, and after a full day of work I still have a couple of basic questions. Here is an example: mydata=data.frame(x=runif(20),y=runif(20),n=runif(20)) mydata2=data.frame(x=c(0.4,0.6,0.5),y=c(0.4,0.4,0.6)) ggplot(mydata, aes(x, y)) + geom_point(aes(size = n)) + geom_polygon(data=mydata2,aes(x,y,alpha=0.5)) In this plot, the

Dear list, I?m having a little trouble with adding vertical lines to a histogram. I need to draw a matrix of histograms (using facets), and in each histogram add a vertical line indicating the mean value of the data in each facet. According to the last example in the geom_hline help, to display different lines in each facet I need to provide a data frame. I modified this example to make a plot

Dear list, I´m calculating time differences between series of time stamps and I noticed something odd: If I do this... > time1=strptime("2009 05 31 22 57 00",format="%Y %m %d %H %M") > time2=strptime("2009 05 31 23 07 00",format="%Y %m %d %H %M") > > diff(c(time1,time2),units="mins") Time difference of 10 mins .. I get the correct

Dear list, I´m using the mgcv package to model the proportion by weight of certain prey on the stomach content of a predator. This proportion is the ratio of two weights (prey weight over stomach weight), and ranges between 0 and 1. The variance is low when proportion is close to 0 and 1, and higher at intermediate values. It seems that the best way to go is to model this using the

Hi, I have a problem. I have a data frame looking like: ID val A? .3 B? 1.2 C? 3.4 D? 2.2 E? 2.0 I need to CREATE the following TABLE: CASE?? DIFF A-A??? 0 A-B??? -0.9 A-C??? -3.1 A-D??? -1.9 A-E??? -1.7 B-A??? ... B-B??? ... B-C B-D B-E C-A C-B C-C C-D C-E D-A D-B D-C D-D D-E E-A E-B E-C E-D E-E WHERE CASE IS THE COUPLE OF ELEMENTS CONSIDEREDM AND DIFF IS THE computed DIFFERENCE between

Hello I have some strange output from R and I try to understand how R works. Could you please help me with that? temp <- rbind (c(10,1),c(99,98)) > temp [,1] [,2] [1,] 10 1 [2,] 99 98 > dist(temp) 1 2 131.6435 > sqrt(dist(temp)) 1 2 11.47360 so far so good. until the nex line: when I try to do what i did before but adding the 1/(what I did

Hello! I have a staff member abroad and need to provide him with the ability to make local calls. The features I need are: * Possibillity to make calls at local (Icelandic) charges from Ireland office. * Possibillity to call the local Icelandic number and reach the Ireland office. I'm also wondering if there is any isdn based solution since there is a possibillity of another staff

Hi all, I would like to propose the attached function ASCIIfy() to be added to the 'tools' package. Non-ASCII characters in character vectors can be problematic for R packages, but sometimes they cannot be avoided. To make packages portable and build without 'R CMD check' warnings, my solution has been to convert problematic characters in functions and datasets to escaped

I present you with a function that solves a problem that has bugged me for many years. I think the problem may be general enough to at least consider adding this function, or a revamped version of it, to the 'stats' package, with the other multinomial functions reside. I'm using R to export data to text files, which are input data for an external model written in C++. Parts of the

the files when you attempt to rename it. This is caused by Window's Media Player loading the file when you click on it. To work around this I had to go into Windows Explorer and change the folder options from "Enable Web Contents in Folders" to "Use Windows Classic Folders". This way, Windows Media player won't load the file when you click on it. Just trying to save

I am looking for a fast way to count the number of rows in a matrix are identical to a pattern vector. For example, if I am interested in counting the number of row vectors in a matrix that are identical to (1,2,3) what would I do? I have tried the identical statement in a loop but this is far too slow. I have a very large matrix and need to avoid loops at all costs. Thanks for any help.

Dear all, I am a new user of R. I would like to know how to get fund's returns in percentage (%). For example, I use: R <- ts(read.xls("FundData"), frequency = 12, start = c(1996, 1)) Whith this program, the returns are like 0.0152699. But, I would like to have 1.52%. Please advise me about the function. Thanks! Fabrice

Hi ! I want to install a Telephone IP Avaya 4610SW in my Asterisk 11, but I cant install. It asks a TFTP/HTTP Server, but is necessary I install it in mu Asterisk Server for works my Telephone? The manual is here https://downloads.avaya.com/css/P8/documents/003880182 Thanks in advanced.

The weighted.mean() function replaces NA values with 0.0 when the user specifies na.rm=TRUE: x <- c(101, 102, NA) mean(x, na.rm=TRUE) # 101.5, correct weighted.mean(x, na.rm=TRUE) # 67.66667, wrong weighted.mean(x, w=c(1,1,1), na.rm=TRUE) # 67.66667, wrong weighted.mean(x, w=c(1,1,1)/3, na.rm=TRUE) # 67.66667, wrong The weights are

Hello fellow R's, I'm sure there must be an easy way to do this. But after digging in the documentation and thinking about it for a while I couldn't figure it out. I need to get a decreasing recursive vector in. I mean something like this: if starting at 2, and ending at 6, the vector should be 2 3 4 5 6 3 4 5 6 4 5 6 5 6 6 An easy way would be to do this x <-

One descriptive statistic that is conspicuously missing from core R is the statistical mode - the most frequent value in a discrete distribution. I would like to propose adding the attached 'statmode' (or a similar function) to the 'stats' package. Currently, it can be quite cumbersome to calculate the mode of a distribution in R, both for experts and beginners. The lack of a

Hi, I just installed jEdit but have no clue, whether I can run my code a'la "ctrl-R" directly from jEdit script, or should source it from R command line, after saving it first in jEdit. thanks for any help, rob -- View this message in context: http://www.nabble.com/jEdit-for-R-tf4684065.html#a13384782 Sent from the R help mailing list archive at Nabble.com.

The model frame shows the response and predictors in a data frame with nicely labelled columns: fm <- lm(wt~qsec+log(hp)+sqrt(disp), data=mtcars) model.frame(fm) # ok When the left hand side consists of more than one response, those response variables still look good, inside a matrix: fm <- lm(cbind(qsec,hp,disp)~wt, data=mtcars) model.frame(fm)[[1]] # ok A problem arises when

Hello list, I read in a txt file using <B<-read.table(file="data.snp",header=TRUE,row.names=NULL) by specifying the row.names=NULL so that the rows are numbered. Below is an example after how the table looks like using <B[1:10,1:3] SNP Chromosome PhysicalPosition 1 SNP_A-1909444 1 7924293 2 SNP_A-2237149 1 8173763

I have been reading about autocorrelation in linear models over the last couple of days, and I have to say the more I read, the more confused I get. Beyond confusion lies enlightenment, so I'm tempted to ask R-Help for guidance. Most authors are mainly worried about autocorrelation in the residuals, but some authors are also worried about autocorrelation within Y and within X vectors