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Hi Just a quick problem that I hope is simple to resolve. I'm doing some work with zero inflated poisson models using the pscl package. I can build models using zeroinfl and get outputs fom them with no problem, but when I try to use the predict.zeroinfl function, I get Error: could not find function "predict.zeroinfl". I was using an older version of R, but still had the same

scatterplot() is autogenerating a regression and loess line. I want to remove the loess line, but can only find samples for how to add it. I definitely do not have code that adds it (see below), so I am puzzling... scatterplot(Aroused ~ anxious | group, data=data, xlab="Aroused", ylab="Anxious", main="Arousal and anxiety ratings", xlim=c(0.5, 9.5),

Hello, I wrote a class like so: > rcfdpsuperclass <- setRefClass( > Class="rcfdpsuperclass", > fields = list( > RcfpdVersion = "character"), > methods = list( > initialize = function(){ > 'Populates fields with defaults and lock as appropriate' > initFields( > RcfpdVersion =

I know when I enter this into R: > x = c(15, 10, 13, 7, 9, 8, 21, 9, 14, 8) > y = c(15, 14, 12, 8, 14, 7, 16, 10, 15, 12) > t.test(x,y,alt="less",var.equal=TRUE) it shows: Two Sample t-test data: x and y t = -0.5331, df = 18, p-value = 0.3002 alternative hypothesis: true difference in means is less than 0 95 percent confidence interval: -Inf 2.027436 sample

Suppose you have the following code: ########## Start code########## data(Chem97, package="mlmRev") densityplot(~gcsescore | factor(score), groups=gender, data=Chem97, auto.key=TRUE, plot.points=FALSE, ref=TRUE, panel=function(x,...){ panel.densityplot(x,...) median.values <- median(x)

Hi Experts, As i am a new in this forum, let me introduce myself:- i am Debaranjan, from India, Assam. I have heard many things about R and its statistical Magic feature. i am really have nothing knowledge about R language nor have ever used before. i am only a nursery in R. please help me in learning R. I have gone through many study material for R but have gain nothing

As an example data set: set.seed(1) z.Date <- as.Date(paste(2003, 02, c(1, 3, 7, 9, 14), sep = "-")) z <- zoo(cbind(left = rnorm(5), right = rnorm(5, sd = 0.2)), z.Date) tt<-time(z) fmt<-"%b-%d" labs<-format(tt,fmt) plot(z[,1], xlab = "Time", ylab = "") If I plot the data and don't like the format of the x axis I can do this:

Dear all, as you can see from the code I want to create *a panel of 11 contour plots through a iteration process*. I found a thread that address the issue of plotting many contour.plots in the same device, but it does not address my problem! I emphasize that the 11 contour plots must be appeared in the same device through an iteration process and NOT individually! par(mfrow=c(4,3)) # I want them

Hello, Before I start to construct something inferior myself I would like to know if such a plot function is already out there. I have count data of a small survey with a few questions which use a scale from "Strongly disagree" to "Strongly agree" and similar things. What I would like to have for a slide is a plot which shows for each question a line over this scale and the

I have two issues. 1-I am trying to use morphology to identify gender. I have 9 variables, both continuous and categorical. I was using two-step cluster analysis in SPSS because two-step could deal with different types of variables. But the output tells me that an animal is in cluster 1 or 2, it does not give me a probability (ex. 0.70 cluster 2). I also did not want to specify that I want two