similar to: Gaussian mixture models, modelNames: EEV, VEV mclust2002

It is going to be easy question to you. I've started to interest in model-based clustering. Adrian E. Raftery "Recent Advances in Model-Based Clustering: Image Segmentation and Variable Selection" (www.stat.washington.edu/Raftery)showed that we can compare different classification methods using BIC statistic. For diabetes dataset the best model is VVV model with 3 classes- for this

hi, When I try to use the function coordProj {mclust} " coordProj(diabetes[,-1],dimens=c(2,3),what="uncertainy",uncertainty=diabetesModel$uncertainty,parameters=diabetesModel$parameters) " to identify uncertainty, it errors and send this warning message: " Warning message: In coordProj(diabetes[, -1], dimens = c(2, 3), what = "uncertainy", : what

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

Hi All, I have a n x m matrix. The n rows are individuals, the m columns are variables. The matrix is in itself a collection of 1s (if a variable is observed for an individual), and 0s (is there is no observation). Something like: [,1] [,2] [,3] [,4] [,5] [,6] [1,] 1 0 1 1 0 0 [2,] 1 0 1 1 0 0 [3,] 1 0 1 1 0 0 [4,] 0 1 0

Full_Name: Martin Elff Version: 1.5.0 OS: MS Windows 98 Submission from: (NULL) (134.155.91.46) Merging of two data frames by variables with different names (using by.x and by.y) is no longer possible (it was possible in version 1.4.1). Call: mvoteint.classd.matadd <- merge( unique(mvoteint.classd), unique(subset(dimens.mpp,

Hi, I'm trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is

Dear group, I want to use the mclust package on large data, and therefore I want to use a subset in the initial clustering phase. From help(mclust): k: If `k' is specified, the hierarchical clustering phase will use a sample of size `k' of the data in the initial hierarchical clustering phase. The default is to use the entire data set. m2 is a

Dear All, I fear I am badly misunderstanding something fundamental about the mclust package. Please considered the dataset pasted at the end of the email (you can also have a look at http://dl.dropbox.com/u/5685598/dataedges.csv ). Now, I would like to use the info on columns 1,2 and 4 to predict the value in column 3. However, when I run the script below (obg_mining_script.R), I get

Hi, A quick question from a social scientist new to R - how do I get coordProj / plot.Mclust to label the nodes by row names? Using "identify" only gives me the row numbers... Thanks. -- Bobby

Hi, quick question from a social scientist new to R: how do I add labels/row names to the nodes in coordProj / plot.Mclust plots? Apologies if this is a silly question... Thanks. -- Bobby ____________________________________________________________________________________Sick sense of humor? Visit Yahoo! TV's Comedy with an Edge to see what's on, when.

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On 01.04.2013 16:24, Janne Hyv?rinen wrote: > I'm worried about some of the modifications done to the UTF-8 > patch. In commit 2199d086921eb37d249cae0731f334556ec6209d #ifdef > checks were changed from specific FLAC__STRINGS_IN_UTF8 to generic > _WIN32 and the specific defines were later removed in commit >

Hi, I'm trying to use the library mclust for gaussian mixture on a numeric vector. The function Mclust(data,G=3) is working fine but the fitting is not optimal and is using modelNames="E". When I'm trying Mclust(data,G=3,modelName="V") I have the following message: Error in if (Sumry$G > 1) ans[c(orderedNames, "z")] else ans[orderedNames] : argument is

> # >> # Generate the figures (on screen) >> # >> # Image generation - function definition >> pic_onscr<-function(matrix, title, cex_val=1) > + {x11() + par(mgp=c(5,2,0), # axis margins + # (title, > labels, line) + mar=c(7,4,4,2), # plot margins (b,l,t,r) + > las=1) # horizontal labels + plot(matrix, # data to plot + >

# lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > # Input: Data matrix as specified in Data-matrix-format.pdf > # Output: LDA plot > # > # Notes: Missing values (if any) are replaced by the half of the lowest > # value in the entire data matrix. >

hello, i already include the error in blue color word. i hope it can help you to understand my question. if not burden you, please give me a guide how to correct the error or maybe you can correct the coding cause error. thank you. > # lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > #

This is a simple problem, but a mystery to me. I'm trying to grab $Family "Scelionidae" from one dataframe and put it into another dataframe occupied with NA in $Family. The result is a "158" ends up there instead of Scelionidae. Simply put fam$Family[1] <- least$Family[1] If I have made a mistake here, can somebody point it out. I've included the simple

Your data frame fam contains factors. Turn it into character strings using fam$Family = as.character(fam$Family) and try again. It may be helpful if you read up on R's factors, see ?factor. HTH, Peter On Tue, Nov 21, 2017 at 2:14 PM, Glen Forister <gforister at gmail.com> wrote: > This is a simple problem, but a mystery to me. > I'm trying to grab $Family

Hi there, I am a master student in Denmark, and apply R to analyze the drug data. I use the function 'lda' to obtain a linear discriminant object, and then wish to use 'plot.lda' to do the plot on this object like below. drug.lda <- lda(Inhibition ~ NET_CHARGE + PKA_1 + MW + MLOGP, data = drug.class, method = "moment") plot.lda(drug.lda,

Hi, I have done different discriminant function analysis of multivariat data. With the CV=True option I was not able to perform the predict() call. What do I have to do? Or is there no possibility at all? You also need the predicted values to produce a plot of the analysis, as far as I know. Here my code: pcor.lda2<-lda(pcor~habarea+hcom+isol+flowcov+herbh+inclin+windprot+shrubcov+baregr,

Well, ?factor does not say anything about this behaviour (assigning numeric code instead of level of factor). And actually if you do assignment for whole vector the result is different (vector in data frame is changed to factor). > temp2$fff[1]<-vec[1] > head(temp2,2) pokus minuty fff 1 T42 240 3 2 T42 300 <NA> > temp2$fff<-vec > head(temp2,2) pokus