similar to: finite mixture model (2-component gaussian): plotting component gaussian components?

Dear Knowledgeable R Community Members, Please excuse my ignorance -- I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance regarding parameters in 2 functions in the "mclust" package. -------------------- PROBLEM DESCRIPTION -------------------- I have a finite mixture modeling problem -- for example, a 2-component gaussian

Hi there, i´m have vector of kernels. just like: kernels = c('gauss','epan','rectangular') i know there are density.default$kernels, but thats not my question here. my own kernel functions are running and working. my problem is the following is not working: dev.off() par(mfrow=c(3,3)) for(i in 1:length(bw)) { for(j in 1:length(kernels)) {

Both the document and R itself are at 2.6.2 (2008-02-08). When I run in the Windows R console the command lines(density(eruptions, bw=0.1)) found in ? 8.2, I get: Error in plot.xy(xy.coords(x, y), type = type, ...) : plot.new has not been called yet Regards, Olivier Lefevre

> On Oct 9, 2017, at 6:03 AM, Big Floppy Dog <bigfloppydog at gmail.com> wrote: > > Hello Ulrik, > > I apologize, but I can not see how to provide a pdf in place of the density > function which calculates a KDE (that is, something from the dataset in the > example). Can you please point to the specific example that might help? > > Here is what I get: > >

Hi everyone, I have what may appear to be a newbie question, but I have looked everywhere I can think to look and I cannot find an answer. On page 35 of "An Introduction to R" the following command appears: plot(ecdf(eruptions), do.points=FALSE, verticals=TRUE). What is the do.points argument? I know what it does (suppresses printing of the points) but where can I find help on it?

Hi, This is not a HW problem, sadly: I was last in a classroom 30 years ago, and can no longer run off to the instructor :-( I apologize but I cut and paste the wrong snippet earlier and made a typo in doing so, but the result is the same with the more appropriate snippet. require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(data = xx,

Hola comunidad, tengo el siguiente problema con la funcion stat_density2d (estimacion de densidad 2d.) del paquete ggplot2 stat_density2d (mapping = NULL, data = NULL, geom = "density2d", position = "identity", na.rm = FALSE, contour = TRUE, n = 100, ...) de esta función requiero ver el cálculo númerico de la estimación de la densidad, cuento con el siguiente codigo y

library(mvtnorm) # you were misusing "require"... only use require if you plan to library(ggplot2) # test the return value and fail gracefully when the package is missing set.seed( 1234 ) xx <- data.frame( rmvt( 100, df = c( 13, 13 ) ) ) xx2 <- expand.grid( X1 = seq( -5, 5, 0.1 ) # all combinations... could be used to fill a matrix , X2 = seq( -5, 5, 0.1 )

I'm applying a function (Cov.f) defined below to each element of a distance matrix. When I run the code below, I get a warning message (below) and elements of returned matrix [2,3] and [3,2] are not zero as I would expect. Clearly, there is an error... What am I doing wrong? Thanks. --Dale Warning message: In if (h <= phi) { : the condition has length > 1 and only the first element

Hello Ulrik, I apologize, but I can not see how to provide a pdf in place of the density function which calculates a KDE (that is, something from the dataset in the example). Can you please point to the specific example that might help? Here is what I get: require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(faithfuld, aes(waiting,

Dear all, In many cases, I need a plotting region much bigger than the screen (e.g. for maps or for graphs with many labels). A. MS-Windows if I try windows(width=25, height=25, rescale="fixed") it seems to be OK (a screen with scrollbars, exactly what I need) but if I try then plot(faithful$eruptions, faithful$waiting) I receive Error in plot.new() : Outer margins too large

I'm trying to shade part of a density plot. The code I'm trying (using the Old Faithful data as an example) is something like this: # The Old Faithful geyser data data(faithful) d <- density(faithful$eruptions, bw = "sj") plot(d) polygon(d[d$x>4], col = "wheat") I expected that the part of the curve to the right of 4 on the x axis should be shaded, but nothing

Hi, I got the same problem like http://tolstoy.newcastle.edu.au/R/devel/04/11/1204.html R crashes when I use the em function from the mclust package on univariate data and on a special case on bivariate data (when the matrix is not provided as written in the manual). It seems as if the problem is the format of the data to be analyzed. Operating System: Windows XP (SP2) R version: R-2.0.1 The

Hi Folks, Like to get some advice on module organization. I have a system that has a few different components. One or more components can be installed on a host. The hosts also have a "type" dimension. This "type" dimension could (should) ideally be used to configure the system (fill in a bunch of variables). Problem is, I''m not sure how the best way to do

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Dear people, I've a problem in doing a power calculation. In Fryer and Nicholson (1993), ICES J. mar. Sci. 50: 161-168 page 164 an example is given with the following characteristics T=5, points in time R=5, replicates Var.within=0.1 q=10, a 10% increase per year The degrees of freedom for the test are calculated as Vl=T*R-2=23 and the non-centrality parameter Dl=4.54. Using this they get a

Hi, I am trying to create a Cumulative Frequency graph and I am using the following example: http://www.r-tutor.com/elementary-statistics/quantitative-data/cumulative-frequency-graph When I plot this data, how do I put in "real values" on the x-axis, rather than the values that are used for the breaks Thanks -- Shane [[alternative HTML version deleted]]

Dear list members, I am using Mclust in order to deconvolute a distribution that I believe is a sum of two gaussians. First I can make a model: > my.data.model = Mclust(my.data, modelNames=c("E"), warn=T, G=1:3) But then, when I try to plot the result, I get the following error: > mclust1Dplot(my.data.model, parameters = my.data.model$parameters, what = "density")

Hi Everybody, Thanks in advance for your help. This is my first time using the foreach statement and I cant get it to work properly so here is what i have test<-function(){ repeat { cand2[l-1]<-rinvgamma(1,phi,lambda[l-1]) q2<-dinvgamma(cand2[l-1],phi,lambda[l-1]) p2<-cand2[l-1]^-1.5*exp(-y[l]^2/(2*cand2[l-1]))*exp(-((log(cand2[l-1])-mu_t_cand[l-1])^2)/2*sigmasq)

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