similar to: Need help with tables

I`ve read all the manuals and still couln`t find what is the difference between the stacked and side-by-side barplots ? Could you explain me ? [[alternative HTML version deleted]]

How to add a mean line in the boxplot keeping the median line ? For example in this: set.seed(1) a <- rnorm(10) b <- rnorm(10) boxplot(a, b) [[alternative HTML version deleted]]

Hi, 1. How do I construct 95% prediction interval for new x values, for example - x = 30000? 2. How do I construct 95% confidence interval? my dataframe is as follows : >dt structure(list(y = c(26100000, 60500000, 16200000, 30700000, 70100000, 57700000, 46700000, 8600000, 10000000, 61800000, 30200000, 52200000, 71900000, 55000000, 12700000 ), x = c(108000, 136000,

Hi I have used a polycor package for categorical correlation coefficients. I run the following script. But there were no results. Could you tell me how to correct the script? Thanks in advance, vars <- names(sdi) for (i in 1:length(vars)) { for (j in 1:length(vars)) { paste(vars[i]," and ", vars[j]) polychor(vars[i], vars[j]) # corr } } -- Kum-Hoe Hwang, Ph.D.Phone :

Hi, I would like to estimate something like y = a + b*d2*y + c*d3*y where the dummies are created from some vector d with three (actually many more) levels using factor(). But either there is included the variable y or d1*y. How could I get rid of these? Example: x = c(1,2,3,4,5,6,7,8) y = c(3,6,2,8,7,6,2,4) d = c(1,1,1,2,3,2,3,3) fd = factor(d) lm(x ~ fd*y) gives: Coefficients: (Intercept)

Dear all, I am new to R. I wish to use R's multiple imputation to deal with missing data. I have a data set with the size around 300 observations and 150 variables. I checked the help function in R and could not locate how to write the codes for this. can anyone give a hand? Do appreciate your time and kindness! Q. [[alternative HTML version deleted]]

Hi, I try to calculate Kendall's W coefficient and I have a bizarre error. little.app.mat<-matrix(c(1,3,4,2,6,5,2,4,3,1,5,6,3,2,5,1,5,4),nrow=3,byrow=TRUE) print(kendall.w(little.app.mat[-1,])) >>> Kendall's W for ordinal data >>> W = 0.7753623Error in if (is.na(x$p.table)) { : argument is of length zero

Hi. Please, how can I put together 2 or more lines at the same scatterplot ? Example: measures of protein intake (quantitative) of 4 children over 30 days, by day. How to plot all children at same graphic: Protein X Time ? Is there any command like "overlay" ? Thank you, Mauricio

Hello, I am trying to model an intensity function with time-varying covariates. Before, I have successfully defined a log likelihood function for a Power-Law Process (lambda(t)=alpha*beta*t^(beta-1)) with two paramters and no covariates for a repairable systems with failure times (t). This function was maximized with R optim. No problem! But now I want to include a covariate indicating a

The expected number of bladder cancer over next 20 years a tire industry is 1.8. Poission distribution is assumed to hold and 6 reported deaths are caused by bladder cancer among the employees. Trying to find how unusual this event is. > ppois(q=6, lambda=1.8, lower.tail = TRUE, log.p = FALSE) [1] 0.9974306 not sure if ppois is the right one to use and the parameters... thx much

I'm sorry to all those who are tired of seeing my email appear in need of help. But, I've never coded in any program before, so this has been a difficult process for me. Is there a simple function to test for colinearity in R? I'm running a logistic regression and a linear regression. Thanks for the help! [[alternative HTML version deleted]]

Dear listmembers, I have a little question: I have my data organized as follow sic level area a 211 2.4 b 311 2.3 b 322 0.2 b 322 0.5 c 100 3.0 c 100 1.5 c 242 1.5 d 222 0.2 where levels and sics are factors. I'm trying to obtain a matrix like this: level 211 311 322 100 242 222 sic a 2.4 0 0

Hi, I have a problem with aggregate. x <- aggregate(t1,list(t2,t3,t4), mean) z<-x[,3] I want z to be a vector but it is a factor. I've tried to use as.vector(z,mode="numeric") but then the numbers get scrambeled. Any help is appriciated /anders

Hi all, I would greatly appreciate some help understanding how R references arrays, matrices, lists, and objects using [[]] and []. I have read the R guides and several tutorials but I am not the fastest kid on the block so I am still having difficulty understanding this. For examples the following code produces a 5 element list of 2X5 random numbers that I then convert to a 2X5X5 matrix.

Hello, I do this a=c(10.2,0.4,0.2,5.2,8.6,1.6,0.0,1.0,6.3,1.4,0.4,0.2) b=matrix(a,nrow=4) rownames(b)=c("20/04/2002","21/04/2002","22/04/2002","23/04/2002") colnames(b)=c("p1","p2","p3") barplot(b,beside=T,col=(c("red","orange","yellow"))) then I have

Hi, I'm having some problems with a bubble plot (ps package). I don't want tick marks on all four sides (just two), I want to have a smaller font size, and I would like to be able to define bubble sizes shown in the legend (now it shows 0, 0, 0, 9.747 and 4265.757 which is not really convenient. Passing some of the standard plot arguments didn't help (in fact, nothing changed).

Dear all R users, I want to insert the R logo in every graphic that I made in my Statistical analysis using R. Can anyone tell me whether is it possible or not and if possible how to do this? your help will be highly appreciated. Thanks and Regards, Arun [[alternative HTML version deleted]]

Hi, I have Forecast Class and Observed Class in a data matrix as below. > Sample1 FCT OBS 1 1 5 2 2 4 3 3- 3+ 4 3 3 5 3+ 3- 6 4 2 7 5 1 I want to find the difference between Observed and Forecast Classes. How can I get this done? I tried to following to convert the 1 through 5 classes, to 1 through 7 for both OBS and FCT column. > Sample1$OBS2 <- Sample1$OBS

Dear R helpers, I am trying to read a CSV file in R called EUROPE (originally an Excel file which I have saved as a CSV file) using the command EUROPEDATA <- read.csv("EUROPE.csv") EUROPE.csv is basically a matrix of dimension 440*44, and has a line of headers, i.e. each column has a name. Using read.csv I can't load the data into R properly. Although the first 20 columns or

Dear All, I am trying to calculate the Hardy-Weinberg Equilibrium p-value for 42 SNPs. I am using the function HWE.exact from the package "genetics". In order not to do a lot of coding "by hand", I have a for loop that goes through each column (each column is one SNP) and gives me the p.value for HWE.exact. Unfortunately some SNP have reached fixation and HWE.exact requires a