search for: mstep

...imit the number of clusters. I want to do a simulation for a fixed number of components, and thus I would like to avoid the unnecessary computations. Is there any difference between hc(modelName=VVV) and hcVVV or hc(modelName=EEE) and hcEEE, etc.? Likewise, are there any differences between mstep(modelName=VVV) and mstepVVV or mstep(modelName=EEE) and mstepEEE, etc. If not, why do the same functions have different names? --------------------------------- [[alternative HTML version deleted]]

...-2.0.1 The following example causes a crash of R: # univariate example require(mclust) X <- c(rnorm(100, mean=1), rnorm(100, mean=5)) # I also tried: X <- as.matrix(c(rnorm(100, mean=1), rnorm(100, mean=5))) Xmap <- cbind(c(rep(1, 100), rep(0, 100)), c(rep(0, 100), rep(1, 100))) Xm <- mstep(modelName="V", data=X, z=Xmap) # CRASH: em(modelName=Xm$modelName, data=X, mu=Xm$mu, sigmasq=Xm$sigmasq, pro=Xm$pro) For bivariate data the following example works: # bivariate example require(mclust) Y <- as.matrix(cbind(c(rnorm(100, mean=1), rnorm(100, mean=5)), c(rnorm(100, mean=...

...but not sure how to do. In the help manual, it specify that in "pro" of the argument "parameter", if the model includes a Poisson term for noise, there should be one more mixing proportion than the number of Gaussian components. But in the example, the parameter is specified by mstep() function, while the mstep() function says for arguement "z", in analyses involving noise, this should not include the conditional probabilities for the noise component. I am confused... Also how to specify the model-specified parameters in the em() function besides just mean and varianc...

...1; //get direction vector of side 1 of the 2D cylinder projection s1.Set(ProjCyl.mPts[1].x - p1.x, ProjCyl.mPts[1].y - p1.y); int n1 = max((int)(mag(s1) / mStep + 0.5), 4); //compute number of points sampled (sample at least 4) float d1 = 1.0f / (float)n1++; //get fraction of side length per sample const P...

I keep on receiving the message below after submitting the following line using the mclust package. m2 is a 99 X 1 column vector. * em(modelName = "E", m2, mu = c(25, 50), sigmasq=10, pro = c(0.4, 0.6)) Error in as.double.default(data) : (list) object cannot be coerced to double. Why do I receive this error? Thank, Brian C. Newquist Research Statistician

...1/2*matrix(rep(1,200*2), 200, 2)) out$parameters # the algorithm does not recover the actual parameters! ######################################### In particular, each time the algorithm returns the same mean for both populations! I also tried the em() function with an initialization given by mstep (), just as in the example in help(em). Please let me know. Thanks. Ery Arias-Castro [[alternative HTML version deleted]]