similar to: how to use mle with a defined function

Suppose I know the value of cumulative bivariate standard normal distribution. How can I solve correlation between variables? Pekka --------------------------------- [[alternative HTML version deleted]]

Hello, I'm quite new with R and so I would like to know if there is a command to calculate an integral. In particular I simulated a bivariate normal distribution using these simple lines: rbivnorm <- function(n, # sample size mux, # expected value of x muy, # expected value of Y sigmax, # standard deviation of

I am experiencing some odd behavior with the .Call interface, and I am hoping someone out there can help me with it. Below is a simple example (in that there are R packages that do exactly what I want), but this code illustrates the problem. Thanks in advance for any help you can provide. Suppose I want to compute the log density of a multivariate normal distribution using C code and the gsl

Hi, Does anyone know if the D'agostino test is available with R ? Alex

Hi guys, I have a code in R and it was work well but when I decrease the epsilon value (indicated in the code) , then I am getting this error Error: evaluation nested too deeply: infinite recursion / options(expressions=)? any help please y = 6.8; w = 7.4; z = 5.7; muy = 7; muw = 7; muz = 6; sigmay = 0.8; sigmaz = 0.76; sigmaw = 0.3; betayx = 0.03; betayz = 0.3; betayw = 0.67 s =

Hello I'm a population ecologist and use R for all my stats and modelling. Recently I have been using R to numerically solve integral projection models. This involves constructing several large matrices. The current code by Easterling (Size-specific sensitivity: Applying a new structured population model. Ecology, 2000, 81, 694-708) uses nested loops to construct the matrices. To speed up the

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