similar to: the sample() function

Dear Masters, I have a question to submit consider the following script m<-4.95 obs<-rpois(36,m) # i generate 36 realization from a poisson(m) hist(obs,freq=F) curve(dpois(x,m),add=T,col="red") #i wish to overlay on the histogram the theorical poisson density function errors are returned saing the x vector doesn't contain integers.... really bizarre i can't give

Hello everybody!!!! Quick question, if you'd like to throw a little tip: does anyone knows a function that runs piecewise regression models with coefficients estimation and inferences ? Thank you [[alternative HTML version deleted]]

Egregious, look what just happened few minutes ago while opening up my program and running the scripts > A<-read.table("C:\\Documents and Settings\\ + me\\Desktop\\TESI\\generale.txt",head=T) Errore: non trovo la funzione "read.table" #CAN'T FIND read.table FUNTION!!!??? ARE WE ok??? > > B<-read.table("C:\\Documents and Settings\\ +

Hi folks... check this out.. > GLU<-lme(gluc~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ + haartd+hivdur+factor(arv), + random= ~rt|id, na.action=na.omit) > intervals(GLU)$fixed lower est. upper (Intercept) 67.3467070345 7.362307e+01 7.989944e+01 rt *0.0148050160* 6.249304e-02 1.101811e-01 cd4

I Dears, if that wouldn't take u too much effort I'd like to ask for a swift opinion: I have a alinear (mixed effect) model that I wish to run as a piecewise one. When I predict the values Iget quite some odds and disturbing results: The predicted stright line after the break point is not straight at all, instead behaves like if it was a hig order polynomial or something similar!!!! I

---------- Forwarded message ---------- From: Freddy Gamma <freddy.gamma@gmail.com> Date: 2011/1/21 Subject: TRADUCING lmer() syntax into lme() To: r-sig-mixed-models@r-project.org Dear Rsociety, I'd like to kingly ask to anyone is willing to answer me how to implement a NON NESTED random effects structure in lme() In particular I've tried the following translation from lmer to

Hello Masters, wishing you all a great 2011 I was also going to ask if anyone knows a quick and efficient way to plot a regression plane (z~x*y). I have tried the regr2.plot{HH} function but it is only an educational tool and has poor graphical properties. I also tried to run the following script on a fictitious longitudinal problem, with poor results set.seed(1234)

Dear Masters, first I'd like to wish u all a great 2011 and happy holydays by now, second (here it come the boring stuff) I have a question to which I hope u would answer: I run a logistic regression by glm(), on the following data type (y1=1,x1=x1); (y2=0,x2=x2);......(yn=0,xn=xn), where the response (y) is abinary outcome on 0,1 amd x is any explanatory variable (continuous or not)

Hello Masters, I run the loess() function to obtain local weighted regressions, given lowess() can't handle NAs, but I don't improve significantly my situation......, actually loess() performance leave me much puzzled.... I attach my easy experiment below #------SCRIPT---------------------------------------------- #I explore the functionalities of lowess() & loess() #because I have

Dear Germano, Thank you for your fast reply, In the above code, *MYData *is the actual data set. Do not we need to convert *MYData to *the dissimilarity matrix using *pam(as.dist(**MYData**), k = 10, diss = TRUE*)* code line?* *Regards.* On Thu, Aug 17, 2017 at 2:58 PM, Germano Rossi <germano.rossi at gmail.com> wrote: > try this > > MYdata <-

Hi Dears, When I introduce an interaciton in a piecewise model I obtain some quite unusual results. If that would't take u such a problem I'd really appreciate an advise from you. I've reproduced an example below... Many thanks x<-rnorm(1000) y<-exp(-x)+rnorm(1000) plot(x,y) abline(v=-1,col=2,lty=2) mod<-lm(y~x+x*(x>-1)) summary(mod) yy<-predict(mod)

Someone knows the existence of a function to sum the elements of the same place A[i,j] B[i,j] of a matrix?thank you -- Dr. Daniele Riggi, PhD student University of Milano-Bicocca Department of Statistics Building U7, Via Bicocca degli Arcimboldi, 8 20126 Milano, Italy cell. +39 328 3380690 mailto: daniele.riggi@gmail.com [[alternative HTML version deleted]]

Dear R-users, I'm working with the Rpart package and trying to understand how the procedure select the best split in the case the method "class" and the splitting index "Gini" are used. In particular I'd like to have look to the source code that works out the best split for un unordered predictor. Does anyone can suggest me which functions in the sources I should

Hi, I would like to know if it is possible to have a "R code" to estimate the parameters of a mixture of bivariate (or multivariate) normals via EM Algorithm. I tried to write it, but in the estimation of the matrix of variance and covariance, i have some problems. I generate two bidimensional vectors both from different distribution with their own vector means and variance and

Hi R-users,I'm trying to solve a non linear equation, to find the degrees of freedom of a mixture of t student. I'm sure i wrote the minimization equation in the right way, but when i try to run the EM algorithm to estimate the parameters of the mixture, the following error will appear: Error in uniroot(function(z) log(z/2) - digamma(z/2) + 1 - log((z + d)/2) + : f() values at end

Dear R users, I am in trouble using the function solve(matrix) in a loop. When it happens that I have a singular matrix, I get an error message saying so and the loop stops. My question is if there in any way to keep on going in the loop. Thank you in advance, Laura *---------------------------------------------------------* Laura Antolini, PhD Department of

Sorry, I never use pam. In the help, you can see that pam require a dataframe OR a dissimilarity matrix. If diss=FALSE then "euclidean" was use.So, I interpret that a matrix of dissimilarity is generated automatically. Problems may be in your data. Indeed pam(ruspini, 4)$diss write a dissimilaty matrix while pam(MYdata,10)$diss wite NULL 2017-08-17 16:03 GMT+02:00 Sema Atasever

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Dear Gregory R. Warnes, I'm a phd student in statistics, at the University of Milano Bicocca. I'm interested to the methods of estimate the parameters of the Dirichlet distribution. Do you have implemented an algorithm in R? If so, can you give me the script? or, in general, some helps? Best Regards Gianna --------------------------------------------------------------- Gianna Monti

Dear R-listers, I would like to carry out a very basic descriptive analysis of homicides rates in Italy, taking into account both the spatial dimension (103 provinces) and the temporal dimension (10 years), but no covariates. In practice, what I would like to do is to describe spatio-temporal variation of homicide rates, identifying those combinations of province-year where the homicide rate