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While I think total compatibility is not possible or even very important I have become aware recently of some fairly low level incompatibilities that have rather serious consequences for interchange between systems. Some of these are possibly well known, but I put them on on record here just in case. (I do not expect any action on these, of course, but people may want to note them, and correct

While I think total compatibility is not possible or even very important I have become aware recently of some fairly low level incompatibilities that have rather serious consequences for interchange between systems. Some of these are possibly well known, but I put them on on record here just in case. (I do not expect any action on these, of course, but people may want to note them, and correct

Using R-2.12.1 and latticeExtra-0.6-14, I would like to understand why a rootogram displaying samples from the Poisson distribution looks like I expected it, whereas a rootogram using the normal distribution does not: library(latticeExtra) rootogram(~rpois(1000, lambda = 50), dfun = function(x) dpois(x, lambda = 50)) rootogram(~rnorm(1000), dfun = function(x) dnorm(x,mean(x),sd(x))) I probably can't attach figures here. Thus a textual description of what I get may suffice: With increasing sample size, the rootogram using random samples from the Poisson distribution s...

Is there any R function that computes the convolution of the double exponential distribution? If not, is there a good way to integrate ((q+x)^n)*exp(-2x) over x from 0 to Inf for any value of q and for any positive integer n? I need to perform the integration within a function with q and n as arguments. The function integrate() is giving me this message: "evaluation of function gave a

...-2.12.1 and latticeExtra-0.6-14, I would like to understand > why a rootogram displaying samples from the Poisson distribution looks like > I > expected it, whereas a rootogram using the normal distribution does not: > > library(latticeExtra) > rootogram(~rpois(1000, lambda = 50), dfun = function(x) dpois(x, lambda = > 50)) > > rootogram(~rnorm(1000), dfun = function(x) dnorm(x,mean(x),sd(x))) > > I probably can't attach figures here. Thus a textual description of what I > get may > suffice: With increasing sample size, the rootogram using random samples...