similar to: superscript text on graph legend

# Hi there, # I am trying to apply a function over a moving-window for a large number of multivariate time-series that are grouped in a nested set of factors. I have spent a few days searching for solutions with no luck, so any suggestions are much appreciated. # The data I have are for the abundance dynamics of multiple species observed in multiple fixed plots at multiple sites. (I total I

Dear all, I want to put 9 barplots side by side. My code below only print 5 names from 9 names I gave. Problem: how to print all of those 9 names? I use cex=0.8 but did not work, it gave me error message. d<-matrix(rpois(45,3),5,9) barplot(d,beside=T,col=rainbow(5),names=c("CRTL","LSB","ONEMKR",

Hi all, How can one evaluate NAs in a numeric dataframe column? For example, I have a dataframe (demo) with a column of numbers and several NAs. If I write demo.df >= 10, numerals will return TRUE or FALSE, but if the value is "NA", "NA" is returned. But if I write demo.df == "NA", it returns as "NA" also. I know that I can remove NAs, but would like

hi, sorry for the potentially stupid question. I'm a little stuck. when trying to run the stupid update manager i need for my satnav, which - obviously - is windows only, nothing happens. install worked, the icon's on my desktop, it has been made executable, but after a bit of harddrive action nothing happens. terminal says: Code: mzwo at mzwo-laptop:~$ env

Hi, I ran two svm models in R e1071 package: the first without cross-validation and the second with 10-fold cross-validation. I used the following syntax: #Model 1: Without cross-validation: > svm.model <- svm(Response ~ ., data=data.df, type="C-classification", > kernel="linear", cost=1) > predict <- fitted(svm.model) > cm <- table(predict,

Hi , can any one help in this problem According to some study, the height for Northern European adult males is normally distributed with an average of 181 centimeter and a standard deviation of 7.3 centimeter. Suppose such an adult male is randomly chosen. Let X be height of that person. The next 3 questions correspond to this information. The answer may be rounded up to 3 decimal places of the

Dear r-helpers, I have a question about multiple testing. Here an example that puzzles me: All matrixes and contrast vectors are presented in treatment contrasts. 1. example: library(multcomp) n<-60; sigma<-20 # n = sample size per group # sigma standard deviation of the residuals cov1 <- matrix(c(3/4,-1/2,-1/2,-1/2,1,0,-1/2,0,1), nrow = 3, ncol=3, byrow=TRUE, dimnames =

I'm trying to make a set of contour plots of bivariate kernel density estimates, showing three such plots overlaid, similar to this plot http://euclid.psych.yorku.ca/SCS/Private/Test/ridge-boot2.pdf except that I would like to have the contours *filled* (using transparent colors). To make this reproducible, I've saved the results of KernSmooth::bkde2D() in the following file:

Dear all, I know there are 'coef', 'predict', 'fit' to get the corresponding outputs. Is that possible to get the value of R-squared from a 'lm' output? Many thanks.

Dear members, I want to create 8 graphs and write it into one page using mfrow=c(4,2). How to make all graphs (including the titles, legends, line types) to be scale down (resized proportionally). As an illustration, below is the code: pdf("testmfrow.pdf") par(mfrow=c(4,2)) x<-seq(1:10) y1<-rnorm(10) y2<-rnorm(10,mean=2,sd=1) y3<-rnorm(10,mean=3,sd=1)

Hi, Is there a way to set the scale of a plot (i.e. number of axis units per centimeter) when you output it to postscript? If not, how am I supposed to plot graphs with different axis limits to the same scale? They just get resized to fit the paper so that graphs which show a smaller number of axis units end up with a larger scale. Cheers, Ben -- Dr. Ben Kenward Department of Psychology,

Dear R Helpers, I have noticed that when I use lmer to analyse data, the summary function gives different values for the AIC, BIC and log-likelihood compared with the anova function. Here is a sample program #make some data set.seed(1); datx=data.frame(array(runif(720),c(240,3),dimnames=list(NULL,c('x1','x2','y' )))) id=rep(1:120,2); datx=cbind(id,datx) #give x1 a

Hi I've suddenly lost access to some permanent cross-server shares. I think this was following the Nov 5 new kernel, rather than the Centos version upgrade. I don't see any difference to man mount.nfs I have:- [root at hs6 ~]# mount hs8:/data /sysback/hs8-data -v mount: no type was given - I'll assume nfs because of the colon mount: trying 172.26.0.8 prog 100003 vers 3 prot tcp port

Hi, I wonder whether the mechanism of parsing parameters to functions has changed between 0.63.1 and 0.63.3? The following code yeils different results in R 0.63.1 (Version 0.63.1 (Dec 5, 1998)) and R 0.63.3. cave<-function(x,a,b) { return(c(mean(x[a],na.rm=T),mean(x[b],na.rm=T))) } datx <- data.frame(rbind(c(1,2,3,4),c(4,5,6,7)))

Hi, I wonder whether the mechanism of parsing parameters to functions has changed between 0.63.1 and 0.63.3? The following code yeils different results in R 0.63.1 (Version 0.63.1 (Dec 5, 1998)) and R 0.63.3. cave<-function(x,a,b) { return(c(mean(x[a],na.rm=T),mean(x[b],na.rm=T))) } datx <- data.frame(rbind(c(1,2,3,4),c(4,5,6,7)))

Hello, I am constructing a nomogram using cph and nomogram commands in Dr. Harrell's Design/RMS package. The HR that I obtain for dichotomous and categorical variables are identical to those that I obtain using STATA stcox. However, the inter-quartile HR I obtain for continuous variables is obviously different, since STATA gives me HR for each unit (year, centimeter, etc) like coxph would

There appear to be reports in the literature that transform continuous independent variablea by the use of splines, e.g., assume the dependent variable is hot dogs eaten per week (HD) and the independent variable is waistline (WL), a normal linear regression model would be: nonconfusing_regression <- lm(HD ~ WL) One might use a spline, confusion_inducing_regression_with_spline <- lm(HD

I am trying to fit a nonlinear regression to infiltration data in order to determine saturated hydraulic conductivity and matric pressure. The original equation can be found in Bagarello et al. 2004 SSSAJ (green-ampt equation for falling head including gravity). I am also VERY new to R and to nonlinear regressions. I have searched the posts, but am still unable to determine why my data come up

I thought this had been fixed with newer kernels? We have an old Maxtor Snap Server, an 80 GB NAS unit, containing some of our archives. Both of our CentOS servers have it permanently mounted by NFS for convenient access. This weekend, I discovered remotely that, although all systems except the VRTSralus remote agents for Veritas (now Symantec) Backup Exec were working just fine, both servers

Well, one way to do it is xyplot(y~time|id, data=dat,type='l', panel=function(x,y,subscripts,...){ panel.xyplot(x,y,subscripts,...) panel.abline(v=dat[subscripts,"cm1"]) panel.abline(v=dat[subscripts,"cm2"]) } ) Since I don't know what the dataframe 'mergeData' is I have used 'dat'. Best regards Frede Aakmann