Hi Ken, I know your question was specifically about the mclus, but you can also try to fit a univariate gaussian mixture using the normalmixEM in the mixtools package.
library(mixtools) out = normalmixEM(data, k=3) That's what I got for your sample: > out$lambda [1] 0.119 0.647 0.234 > out$mu [1] 0.180 0.002 -0.092 > out$sigma [1] 0.077 0.026 0.078 If you wanna visualize the density for each component, use: plot.mixEM(out, density=T) I hope this helps, Tatiana Benaglia Ph.D. Candidate Department of Statistics Penn State University On Oct 3, 2007, at 6:47 PM, Lo, Ken wrote: >> No HTML this time. Sorry > > Dear all, > > I am attempting to model some one-dimensional data using Gaussian > mixture model with mclust. Generally, the data that I have have 3 > overlapping populations (with one of them being the majority, and > the other two combining to less than 15%) and for some reason, > mclust consistently ignores the smaller peaks, giving me strange > values for the means (completely anti-intuitive in terms of visual > inspection by using plot(density())). However, when I use rnorm to > generate some fake data, mclust works consistently well. As I am > quite new to R, I was wondering whether anyone could help me out. > I am using the em function in mclust, with parameters that are > arbitrarily set > > Pro <- c(0.33,0.33,0.33) > Mean<- c(-0.5,0,0.5) > Sigmasq <- c(0.05,0.05,0.05) > > And a sample of my data set is > > c > (-0.016133,-0.07668,-0.000625,0.031329,-0.011094,0.014199,-0.014141,0. > 036836,-0.007695,-0.011738,-0.021953,0.046565,0.010859,-0.050313,-0.16 > 7813,0.01543,-0.057598,-0.034336,0.182275,0.032959,0.01918,0.009248,-0 > . > 195273,-0.00918,-0.017813,0.003828,-0.113867,0.004014,0.031504,0.00427 > 7,0.052188,-0.030859,-0.214023,-0.329102,-0.07832,-0.008379,0.05833,-0 > . > 007285,-0.036992,0.035768,0.055006,-0.000781,0.005067,-0.025811,0.0210 > 16,-0.002598,-0.036799,-0.03119,-0.004482,-0.024473,-0.108115,-0.11631 > 8,0.158008,0.04252,-0.032129,0.00707,-0.073398,-0.115605,-0.033945,-0. > 022793,0.041855,0.006289,0.250273,0.042607,-0.000449,0.030098,0.041238 > ,-0.028926,-0.111895,0.003867,0.015625,-0.018906,-0.00291,-0.027188,0. > 00957,-0.133369,0.018652,0.138652,0.038789,-0.050107,0.135908,-0.05272 > 5,0.005977,0.030977,0.005371,-0.179902,-0.008691,0.033711,0.164033,-0. > 063457,0.022734,-0.047227,0.025918,-0.005557,-0.104453,0.021348,-0.054 > 902,-0.069277,-0.115273,0.038906,0.171211,0.000645,-0.064873,0.014062, > -0.00252,-0.017715,-0.000586,0.174609,-0.056396,0.000937,-0.217148,-0. > 203105,0.006533,0.015371,-0.024629,0.015244,0.002949,0.024805,-0.10402 > 3,0.007964,-0.198633,-0.007833,-0.000518,0.018232,0.000195,0.028575,-0 > . > 028145,-0.030098,-0.002148,-0.035723,-0.005996,0.023027,0.034512,0.009 > 189,0.049252,-0.016641,-0.023262,-0.013379,-0.013633,0.150996,0.040391 > , > 0.153809,0.001182,0.040371,-0.016191,-0.05097,-0.12041,0.042617,0.0188 > 28,-0.002617,-0.043887,-0.025764,-0.016836,0.023535,0.040625,0.158789, > -0.026934,0.02791,-0.108027,0.037979,-0.011865,0.06127,0.04416,-0.0783 > 3,0.019922,0.000685,-0.071885,0.000479,0.006211,-0.030879,-0.009188,-0 > . > 061895,-0.069102,0.032051,-0.082637,-0.246484,-0.015586,-0.008555,0.26 > 5664,0.050781,0.008242,0.169785,-0.025977,0.017871,-0.239492,0.005234, > 0.006865,0.007344,0.237861,-0.110742,0.208008,0.189336,0.205469,-0.111 > 729,-0.023438,0.49,-0.028281,0.177988,0.00998,-0.002402,0.161924,0.220 > 859,0.026455,0.019629,-0.015098,-0.110771,-0.014414,0.121211,0.028439, > -0.026143,0.024989,-0.060801,-0.023124,-0.012734,0.168398,0.039955,-0. > 038984,-0.028543,0.157412,-0.015547,-0.012617,0.031607,-0.053437,0.027 > 246,0.003906,-0.218613,0.024902,0.020273,0.011914,0.162051,0.00582,-0. > 019189,-0.009029,0.001875,0.015273,0.175303,-0.092441,-0.086738,-0.022 > 871,0.027852,-0.108809,0.005938,-0.016543,-0.019288,0.210566,-0.022813 > ,-0.001748,-0.108574,0.164971,-0.075186) > > If anyone could help me out, I would be extremely grateful. > > Best, > > Ken Lo > > > ********************************************** > Ken Lo, PhD > Post-Doctorate Research Affliliate > Department of Cancer Genetics > Buffalo Life Science Complex, L2-104 > Roswell Park Cancer Institute > Elm and Carlton Streets > Buffalo, New York 14263 > Telephone: 716-845-3941 > Fax: 716-845-3940 > E-mail: [EMAIL PROTECTED] > Web: www.RoswellPark.org > > Located in the > Buffalo Life Science Complex > on the Buffalo Niagara Medical Campus > ********************************************** > > > > > > This email message may contain legally privileged and/or > confidential information. If you are not the intended recipient > (s), or the employee or agent responsible for the delivery of this > message to the intended recipient(s), you are hereby notified that > any disclosure, copying, distribution, or use of this email message > is prohibited. If you have received this message in error, please > notify the sender immediately by e-mail and delete this email > message from your computer. Thank you. > > ______________________________________________ > R-help@r-project.org mailing list > 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. ______________________________________________ R-help@r-project.org mailing list 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.
