similar to: code optimization tips

Dear addresses, I need perform a batch of 10 000 simulations for each of 4 options considered. (The idea is to obtain the parameter estimates in a heteroskedastic linear regression model - with additive or mixed heteroskedasticity - via the Kenward-Roger small-sample adjusted covariance matrix of disturbances). For this purpose I wrote an R program which would capture all possible options (true

Hello, I have a series of questions that I hope will be simple to answer. Basically I would like a code to do the following so that I can compute the distribution free test for the slope of a postulated regression line (Theil test). As I am testing the null hypothesis that slope = 0 against the general alternative the slope does not equal 0, it should be pretty straight-forward. I have a data

Dear R helpers,   I have following input files. (Actually they are more than 10 rates but here i am considering only 2 rates to write my problem)   rate1.csv min1        max1            min2          max2          min3           max3 1.05        1.30               1.30          1.65             1.65          1.99   rate2.csv min1        max1            min2          max2          min3          

hey, i want to generate an excel file and send it directly to the browser (without storing it to the harddisk). does anyone has any solution? thanks in advance this is my code: -------------------- def export_excel if @request.env[''HTTP_USER_AGENT''] =~ /msie/i @headers[''Pragma''] = '''' @headers[''Cache-Control''] =

Here is an example of the data.frame that I have, df<-data.frame("case"=rep(1:5,each=9),"id"=rep(1:9,times=5),"x"=round(runif(length(rep(1:5,each=9))))) "case" represents the cases, "id" the persons, and "x" is the binary state. I would like to know in how many cases any two persons a. both have "1", b. the first has

I am trying to fit a linear mixed model of the form y_ij = X_ij \beta + delta_i + e_ij where e_ij ~N(0,s^2_ij) with s_ij known and delta_i~N(0,tau^2) I looked at the ecme routine in package:pan, but this routine does not allow for different Vi (variance covariance matrix of the e_i vector) matrices for each cluster. Is there an easy way to fit this model in R or should I bite the bullet and

Hi Folks, Given k RVs with MVN distribution N(mu,S) (S a kxk covariance matrix), let (w.l.o.g.) X1 denote the first r of them, and X2 the last (k-r). Likewise, let mu1 and mu2 denote their respective expectations. Then, of course, the expectation of X2 given X1=x1 is mu2 + S21*inv(S22)*(x1 - mu1) and the covariance matrix of X2 given X1=x2 is S22 - S21*inv(X11)*S12 where Sij is the

I''m having difficulty getting my head around some CA issues My client has: [puppetd] ca_server=puppetca.mydomain.com and puppet resolves to a different machine. when puppet connects, it requests a signature from puppetca.mydomain.combut then on the next pass fails with the following: err: Could not retrieve catalog: Certificates were not trusted: SSL_connect returned=1 errno=0

Hello everyone, I wanted to ask if there is an R-package to fit the following Poisson regression model log(\lambda_{ijk}) = \phi_{i} + \alpha_{j} + \beta_{k} i=1,\cdots,N (subjects) j=0,1 (two levels) k=0,1 (two levels) treating the \phi_{i} as nuinsance parameters. Thank you very much -- -Tony [[alternative HTML version deleted]]

*From:* flang-dev <flang-dev-bounces at lists.flang-compiler.org> *On Behalf Of *Eric Schweitz (PGI) *Sent:* Thursday, November 01, 2018 1:02 PM *To:* flang-dev at lists.flang-compiler.org *Subject:* [Flang-dev] RFC: Adding debug information to LLVM to support Fortran In order to support debugging in the Flang project, work has been done to extend LLVM debug information for the Fortran

Dear all, suppose I have a vector with elements as: Vec <- c(2,3,4,5,6) Now I want to have all possible combination of length 3 using those elements and without any repetition. Like, I want to have 1 possibility like 2-3-4 but not 3-2-4. Can somebody guide me how to achieve that in R? Thanks for your help.

my major is bioinformatics, and i'm trying to cluster ( agglomerate the closest pari of observations ) in R. i have already got my own similarities metric, but do not know how to clust it based on similarities instead of dissimilarities. since the help document of hierclust mentions the parameter "sim", which seems good to me, but it doesn't appear in the code of hierclust()

Ok, I''ve been reading and I have some questions about best practices: I understand that modules are to be self contained blocks that i can just drop in. Using best practices, how does this fit into the naming scheme? Classes are singletons. I think i understand this. I''ve been defining classes in /etc/puppet/classes, but then how does this relate to any modules i might want

Hello, I'm trying to fit a special kind of proportional odds model from: Whitehead et al. (2001). Meta-analysis of ordinal outcome using individual patient data. Statistics in medicine 20: 2243-2260. (model 2) The data are as follows: library(nlme) library(geepack) library(Design) library(MASS) options(contrasts=c("contr.SAS","contr.poly")) counts <-

Regarding flags, I was just thinking that maybe we should invent a new DISubprogramFlags type. DISubprogram already has a few bitfields for subprogram-specific things, Fortran will want 3 more, and there's no reason to fill up the generic DIFlags with more bits that are used in only one class. I agree that the array stuff needs to be designed with an eye to handling how other languages do

Is there a way to estimate a nominal response model? To be more specific let's say I want to calibrate: \pi_{v}(\theta_j)=\frac{e^{\xi_{v}+\lambda_{v}\theta_j}}{\sum_{h=1}^m e^{\xi_{h}+\lambda_{h}\theta_j}} Where $\theta_j$ is a the dependent variable and I need to estimate $\xi_{h}$ and $\lambda_{h}$ for $h \in {1...,m}$. Thank you, Mauricio Romero Quantil S.A.S. Cel: 3112231150

Signed-off-by: Scott Seago <sseago at redhat.com> --- AUTHORS | 17 ++++++ README | 10 +++ conf/ovirt-agent | 12 ++++ conf/ovirt-db-omatic | 12 ++++ conf/ovirt-host-browser | 12 ++++

Ben trovati. Ho questa _form : <%= error_messages_for ''requirement'' %> <!--[form:requirement]--> <p><label for="requirement[structure_id]">Struttura</label><br/> <%= @structures = Structure.find(:all, :order => "nome").map {|f| [f.nome,f.id] } select(:structure, :id, @structures) %> <p><label