similar to: univariate normal mixtures

Dear, I have problems with installing R-1.7.1 for Redhat 9. When I applied `./configure' and `make', I get the following error: make check make[1]: Entering directory `/volume1/scratch/jallemee/R-1.7.1/tests' make[2]: Entering directory `/volume1/scratch/jallemee/R-1.7.1/tests' make[3]: Entering directory `/volume1/scratch/jallemee/R-1.7.1/tests/Examples' make[4]: Entering

Dear, I tried to install the DBI package in R-1.7.1, but this gave the following error: /volume1/scratch/jallemee/R/lib/R/bin/INSTALL: line 1: 1856 Done ( echo "options(save.image.defaults=${save_image_defaults})"; if test -s R_PROFILE.R; then cat R_PROFILE.R; fi; echo

Dear ALL I have this function in R: func_LN <- function(data){ med_ge <- matrix(c(rep(NA,nrow(data)*ncol(data))), nrow = nrow(data), ncol=ncol(data), byrow=TRUE) T <- matrix(c(rep(NA,length(n)*ncol(data))), nrow = length(n), ncol=ncol(data), byrow=TRUE) Tdiff<- matrix(c(rep(NA,length(n)*ncol(data))), nrow = length(n), ncol=ncol(data), byrow=TRUE) T1<- c(rep(NA,ncol(data)))

Hi Folks, I am dealing with data which have been presented as at each x_i, mean m_i of the y-values at x_i, sd s_i of the y-values at x_i number n_i of the y-values at x_i and I want to linearly regress y on x. There does not seem to be an option to 'lm' which can deal with such data directly, though the regression problem could be algebraically

Dear, I have a data frame melted from a list of matrices (melt from reshape package), then I impute some missing values and then want to tabulate the data again to the array (or list, doesn't matter) of matrices form. However when using xtabs function it orders my rows alphabetically and apparently doesn't take "reorder = FALSE" option or anything like it. Is there anything I

Hello, I'm looking for a way to plot different data series on one graph. I have a series of hourly rainfall and quarterly flow measurements (i.e. 4 times an hour) of a catchment. The rainfall should be plotted in bars, the flow as a line. Both on the same X axe (time) but with different Y axes. The problem is the plot() function does not support add=TRUE... Furthermore I'm not sure

Dear R users I have a data frame that looks like this: m j X1 X2 1 1 1 2 1 ... 1 J 2 1 2 2 2 ... 2 J . . . M 1 M 2 M ... M J The data frame essentially looks like a panel: m and j are indicators where m is 1:M and j is 1:J (and M > J); X1 and X2 are variables. I

Dear all, I have to handle a large matrix (1000 x 10001) where in the last column i have a value that all the preceding values in the same row has to be compared to. I have made the following code : # generate a (1000 x 10001) matrix, testm # generate statistics matrix 1000 x 4: qnt <- c(0.01, 0.05) cmp_fun <- function(x) { LAST <- length(x) smpls <- x[1:(LAST-1)] real

Greetings, Sorry, the last message was sent by mistake! Here it is again: I encounter a strange problem computing some numerical integrals on [0,oo). Define $$ M_j(x)=exp(-jax) $$ where $a=0.08$. We want to compute the $L^2([0,\infty))$-inner products $$ A_{ij}:=(M_i,M_j)=\int_0^\infty M_i(x)M_j(x)dx $$ Analytically we have $$ A_{ij}=1/(a(i+j)). $$ In the code below we compute the matrix

A few weeks ago, I upgraded Samba 3.0.1x to 3.0.14a . After the upgrade, all completed printjobs on all 40 printers stayed in samba's print queue (they were removed from the unix-printqueue). When I installed 3.0.20rc2, everything back to normal. But since the upgrade this weekend to 3.0.20, the same thing happens again: no jobs were removed from the samba printerqueue's. Removing

I have been authoring a very small R package on CRAN, named "normix" which implements an S3 class "norMix" has plot and print methods; further, E[X] and Var[X] methods, random number generation ("r") and density evaluation. It also provides the 16 "Marron-Wand densities" (known in the (1d) density estimation business). Erik J?rgensen has provided

I have been authoring a very small R package on CRAN, named "normix" which implements an S3 class "norMix" has plot and print methods; further, E[X] and Var[X] methods, random number generation ("r") and density evaluation. It also provides the 16 "Marron-Wand densities" (known in the (1d) density estimation business). Erik J?rgensen has provided

Hi, R-listers I tried to plot several graphs in a sigle x-y coordinate settings, like the following: |(y) s | ****** s | ***** s | sssssssssssssssssss |_______________________________(x) where "*" and "s" denote two diffrent plots. However, when I used plot(data1); % data1 is the data points of "*"

Hello, I am trying to find out if R can do the following: I have a mixture of normals say f = 0.2*Normal(2, 5) + 0.8*Normal(3,2) How do I find the difference in the densities at any particular point of f and at Normal(2,5)? -- Thanks, Jim. [[alternative HTML version deleted]]

hello for exampl, i have this programme # Generating data which are right truncated library(DTDA) library(splines) library(survival) n<-25 X<-runif(n,0,1) V<-runif(n,0.75,1) for (i in 1:n){ while (X[i]>V[i]){ X[i]<-runif(1,0,1) V[i]<-runif(1,0.75,1) }} res<-lynden(X=X,U=NA, V=V, boot=TRUE) attach(res) temps = time M_i = n.event L_t = res

Dear R-help group, I would like to model directly following random effect model: Y_ik = M_ik + E_ik where M_ik ~ N(Mew_k,tau_k^2) E_ik ~ N(0,s_ik^2) i = number of study k = number of treatment --------------------------------------------------------------------------- I have practiced using the command from 'Mixed -Effects models in S and S-plus'

Dear list, Can anyone provide a package or code for estimating the parameters of a mixture of c (c >=2) univariate normal distributions? I've tried the algorithm provided by Venables & Ripley (1999) p 263, for the mixture of two normal, but I don't find the "ms" function in R. I've used nls instead, but I'm not sure if it works the same. The data I have is very

Dear all, ? I am implementing a stochastic utility model that will eventually make use of multinomial logit. I found that there is a package in R called mlogit. I am not sure whether I have already found the correct package or software. May I ask am I correct? ? Basically, let's say ? I have observations of n outcomes, for each outcome 1<=i<=n, they were selected by a choice from a set

Hi, I am running simulations that does multiple comparisons to control. For each simulation, I need to model 7 nls functions. I loop over 7 to do the nls using try if try fails, I break out of that loop, and go to next simulation. I get warnings on nls failures, but the simulation continues to run, except when the internal call (internal to nls) of the chol2inv fails.

Hello! I am new to R (before used python exclusively and would actually call the R solution for this issue inside a python notebook, hope that doesn?t disqualify me right of the batch). Right now I am looking for a piece of software to fit a 1D data sample to a mixture of t-distributions. I searched quite a while already and it seems to be that this is a somehwat obscure endeavor as most