similar to: comparing mixture models (mix function in mixdist package)

Dear R-help, my aim is to fit a constrained 2 component gamma mixture using mix within package mixdist. The constraints being fixing both of the means and both of the sigmas. Thus the only unconstrained parameter I wish to fit is pi the proportions of the mixtures. This is the code I used: PP2Pars<-data.frame(c(0.23,0.77), c(9.174,29.54), c(9.983,12.369));

Dear R users, Please help me on using "mix" function under package "mixdist". My data distribution shows there are two components for the mixture distribution: left part is an exponential and right part is a normal. So I plan to use "gamma" mixture distribution to estimate the parameters. Here is what I am using for the "mix" function. Test<-mix(x,

Hi, All, I fitted a 3-component normal mixture model with the mixdist package in R. How can I get the density of a new data after I fit the model? Is there any function to do it? Thanks, Cindy [[alternative HTML version deleted]]

Hello, I would like to fit a mixture of two Weibull distributions to my data, estimate the model parameters, and compare the fit of the model to that of a single Weibull distribution. I have used the mix() function in the 'mixdist' package to fit the mixed distribution, and have got the parameter estimates, however, I have not been able to get the log-likelihood for the fit of this model

Hi, I am working on a population of an invasive clam. The data are the size of each clam per station (2mm on average). Each station is found at a different distance from a power nuclear station, so at different water temperatures. The fist step I want to do is to identify cohort size at each station or (zone of water temperature). The second step will be to see whether the size or number of

Dear Ingmar & Dave, Thanks a lot for your help and sorry for the late reply. Finally, I've found a way to separate the mixture of distributions (empirically). But the gamlss package looks great, I'm sure it will help me during my further studies. Kind regards, Susanne On 15 Jun 2009, at 20:09, Ingmar Visser wrote: > Dear Susanne & Dave, > > The gamlss package family

Hi,all with my data,there are more than 1000 quantitative results of antibody concentrations, there may be 2 components(positive and negative), or 3 components (may be strong positive, positive, and negative), or 4-6 components. Could you tell me how to determine the number of components of the mixture model? the "anova.mix" in mixdist of the R software seems not work. my

Hi, All, I want to fit a normal mixture model. Which package in R is best for this? I was using the package 'mixdist', but I need to group the data into groups before fitting model, and different groupings seem to lead to different results. What other package can I use which is stable? And are there packages that can automatically determine the number of components? Thank you, Cindy

Dear all, I am attempting to model some one-dimensional data using a mixture model of non-central Student's t distributions. However, I haven't been able to find any R package that provides this functionality. Could there be a way to "manipulate" the EM algorithms from the mixdist or mixtools package to fit the model, or do you have any other suggestions? If anyone could help

Hi list, I'm using barplot2 form the gplots package to plot a few numbers (I want to add SD bars later). However, I would like the y-axis not to start from 0 but 500. When I add the parameters YLIM, something goes wrong. The graph is not 'cut off' at 500. Instead the bars seems to sink trough the bottom of the graph. Because its a little hard to explain, here is a self-containing

Dear R-list, Is there a way to convert the typical long R data-format to a 1-line per subject format? I have data formatted as: Group subj condition variable 1 1 1 746.36625 2 2 1 1076.152857 1 3 1 1076.152857 2 4 1 657.4263636 1 5 1 854.1266667 2 6 1 1191.676154 1 7 1 1028.175385 1 1 2 46.36625 2 2 2 76.152857 1 3 2 76.152857 2 4 2 57.4263636 1 5 2 54.1266667 2 6 2 191.676154 1 7 2 028.175385

Hello, I'm currently trying to find a method to interpolate or smooth data that represent a trajectory in space. For example, I have an ordered (=time) set of (x,y) tuples which constitute a path in a 2D space. Is there a way using R to interpolate between these points in a way similar to spline interpolation so that I get a smooth path in space? Greetings, Dieter -- Dieter Vanderelst

Hi list, I'm currently processing textual data and I would really appreciate some help with one off my problems. I have a set of strings and I want to count how often each of this strings appears in this set. This is not very difficult and can be done as: TB<-table(my_set) plot(TB) However, I also want to collapse across sub-strings. This is, I want a sub-string ss of string S to be

Hi All, I have an R script that spawns output in the form of an HTML page. This is done by the R2HTML package. Now I want to run the same script using Rcmd BATCH. However, it seems that it is not possible to use R2HTML in this case. My script ends with this error message: ######################### Error in dev.print(png, file = AbsGraphFileName, width = Width, height = Height, : can only

Hi all, I'm trying to install the mixdist package with: install.packages("mixdist") But I'm getting the following errors: * installing *source* package ‘mixdist’ ... ** R ** data ** preparing package for lazy loading ** help *** installing help indices ** building package indices ... Warning in utils::data(list = f, package = package, lib.loc = lib.loc, envir = dataEnv) :

Dear all, I am trying to fit a double gaussian to some data using the mixdist package: --- begin code --- ? library(mixdist) ? time <- seq(673,723) ??counts <- c(3,12,8,12,18,24,39,48,64,88,101,132,198,253,331,419,563,781,1134,1423,1842,2505,374,6099,9343,13009, ? ? ? ? ? ? ? ? ? ?15097,13712,9969,6785,4742,3626,3794,4737,5494,5656,4806,3474,2165,1290,799,431,213,137,66,57,41,35,27,27,27) ?

Dear List, I'm trying to interpret the results of the Kruskal's Non-metric Multidimensional Scaling algorithm (isoMDS, MASS package). The 'goodness of fit' is reported as "The final stress achieved (in percent)". What does this mean exactly? I've tried to google for an answer but I've not come up with a definitive answer. Regards, Dieter -- Dieter Vanderelst

Dear R User, I am an electrical engineering student and have just come across a curve fitting problem. I need to find the constituent Gaussian distribution curves fitting the data attached in Workbook1.txt here. I tried to use Mixdist on R but ran into following problem. Can you suggest me where I am going wrong? > super <-read.table("Workbook1.txt",,sep ="\t") >

Hi List, I have a problem plotting data using the lineplot.CI command in the sciplot package. I want to plot the data of 2 experimental cases using different lines (traces). Time is on the X-axis. The tricky thing is that the data collection in the second case started later than for the first case. This is to say: the first n data points for the second case are missing. So far so good. However,

I've been trying with no success to model mixtures of Gamma distributions using the package flexmix (see examples below). Can anyone help me get it to model better? Thanks very much. -Ben ## ## Please help me get flexmix to correctly model mixtures of ## Gamma distributions. See examples below. ## library('flexmix') ## ## Plot a histogram of dat and the Gamma mixture model given