Hello I am trying to calculate the values of the concentration parameters (kappa) and preferred direction (mu) for a Von Mises mixture model. I currently have some R code that gives me optimised values for the product of kappa and mu, but I'm not sure how to calculate them when both are unknown? How could I calculate mu and kappa from y2 if I didn't know either in the 1st place? I what to use movMF to give me values of kappa from some directional data where I don't know either kappa or mu.
## Generate and fit a "small-mix" data set a la Banerjee et al. mu <- rbind(c(-0.251, -0.968), c(0.399, 0.917)) kappa <- c(4, 4) theta <- kappa * mu theta alpha <- c(0.48, 0.52) ## Generate a sample of size n = 50 from the von Mises-Fisher mixture ## with the above parameters. set.seed(123) x <- rmovMF(50, theta, alpha) ## Fit a von Mises-Fisher mixture with the "right" number of components, ## using 10 EM runs. y2 <- movMF(x, 2, nruns = 10) Y2 gives > y2 theta: [,1] [,2] 1 2.443225 5.259337 2 -1.851384 -4.291278 alpha: [1] 0.4823648 0.5176352 L: [1] 24.98124 How could I calculate kappa and mu if I didn't know either in the 1st place? Thanks Peter [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.