similar to: frequency tables and sorting by rowSum

Hello. I am a beginer in R and I can not implement the KhmaladzeTest in the following command. Please help me!!!!!!!!!!! PD: I attach thw results and the messages of the R program R : Copyright 2006, The R Foundation for Statistical Computing Version 2.3.1 (2006-06-01) ISBN 3-900051-07-0 R es un software libre y viene sin GARANTIA ALGUNA. Usted puede redistribuirlo bajo ciertas

I've been trying to draw quantile linear regression lines across a scatterplot of my data using attach(forrq) plot(PREGNANT,DAY8,xlab="pregnant EPDS",ylab="postnatal EPDS",cex=.5) taus <- c(.05,.1,.25,.75,.9,.95) xx <- seq(min(PREGNANT),max(PREGNANT),100) for(tau in taus){ f <- coef(rq(DAY8~PREGNANT,tau=tau)) yy <-

Quantreg package allows to plot the summary of models derived by quantile regression at different taus. The plot shows the parameters variation by varying taus: intercept and slope (for a linear model). Together with these values even confidence intervals may be plotted, based on the threshold given within the summary (e.g. alpha=0.01 equals 99% CI). However the graphic even plots the mean of

Quantile Regression for Longitudinal Data. Hi, I am trying to estimate a quantile regression using panel data. I am trying to use the model that is described in Dr. Koenker's article. So I use the code the that is posted in the following link: http://www.econ.uiuc.edu/~roger/research/panel/rq.fit.panel.R I am trying to change the number quantiles being estimated. I change the codes about

Dear all, I am using the "rq.fit.hogg" function from the "quantreg" package. I have two problems with it. First (less importantly), it gives an error at its default values with error message "Error in if (n2 != length(r)) stop("R and r of incompatible dimension") : argument is of length zero". I solve this by commenting four lines in the code. I.e. I

Hey, My dataset has 1 dependent variable(Logloss) and 7 independent dummy variables(AS,AM,CB,CF,RB,RBR,TS) , it's attached in this email. The problem is I cant finish Khmaladze test because there's an error "Error in switch(mode(x), "NULL" = structure(NULL, class = "formula"), : invalid formula" which I really dont know how to fix. My R version is 2.7.2.

I want to gain thousands of random sampling data by randomizing the presence-absence data. Meantime, one important limition is that the row and column sums must be fixed. For example, the data "tst" is following: site1 site2 site3 site4 site5 site6 site7 site8 1 0 0 0 1 1 0 0 0 1 1 1 0 1 0 1 1 0 0 0 1 0 1 0 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 0 0 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0

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Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N

Dear all, I have just sent an email with my problem, but I think no one can see the red part, beacuse it is black. So, i am writing again the codes: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N <- 200 I <- 5 taus <- c(0.480:0.520) h <-

Hi, I am trying to covert a Winbugs code into R code. Here is the winbugs code model{# model’s likelihoodfor (i in 1:n){time[i] ~ dnorm( mu[i], tau ) # stochastic componenent# link and linear predictormu[i] <- beta0 + beta1 * cases[i] + beta2 * distance[i]}# prior distributionstau ~ dgamma( 0.01, 0.01 )beta0 ~ dnorm( 0.0, 1.0E-4)beta1 ~ dnorm( 0.0, 1.0E-4)beta2 ~ dnorm( 0.0, 1.0E-4)#

Hello, Is there a possibility to use xtable with a vector to generate a latex table? I always get an error, that no applicable method is available. For example: b<-1:12 dim(b)<-c(2,6) dimnames(b)[[2]]<-paste("col",1:6) xtable(b) works fine and does not raise an error, but a<-1:6 names(a)<-paste(col,1:6) xtable(b) does not work. Regards, Stefan

The algorithm does make a differece. You can use Kahan's summation algorithm (https://en.wikipedia.org/wiki/Kahan_summation_algorithm) to reduce the error compared to the naive summation algorithm. E.g., in R code: naiveSum <- function(x) { s <- 0.0 for(xi in x) s <- s + xi s } kahanSum <- function (x) { s <- 0.0 c <- 0.0 # running compensation for lost

I installed dovecot on my system using the following configuration (in dovecot.conf): protocols = imap listen = * ssl_disable = yes login_user = nobody login_processes_count = 3 mail_extra_groups = nobody default_mail_env = maildir:/home/%u/Maildir auth default { mechanisms = plain passdb shadow { } userdb passwd { } user = root } After that I tested via telnet an got the message: Connection

Hello to all, I got samba3 PDC working with ldap. But I' m still wondering how to set important things about the users passwords. The first thing when a user login the first time should be to change his/her password? Where do I set when the passwords expire and how do I set it to 60 days? I do not work mith Microsoft's usrmgr because of Vista clients.I look at my samba/ldap with LDAP

The replay gain code has dos line endings in CVS, which causes problems for the Sun compiler, among others. Attached is a patch for the lazy, but it's probably easier to fix locally and commit. -r

Hello guys, I'm using Winbind to integrate my Active Directory Users into Linux. The Domain is very big and is in trust with four other Domains. I've about 100,000+ users. Sometimes everything works perfect, wbinfo -u and wbinfo -g parse the correct users/groups but when I restart Samba + Winbind it does not work anymore. When I first try wbinfo -m it lists all trusted domains but

Hello, I am trying to write FORTRAN code to do the same as some R code I have. I get (small) differences when using the sum function in R. I know there are numerical routines to improve precision, but I have not been able to figure out what algorithm R is using. Does anyone know this? Or where can I find the code for the sum function? Regards, Rampal Etienne

Hi, I would like to fit the following model with quantile regression: y ~ alpha + beta where both alpha and beta are factors. The conceptual model I have in my head is that alpha is a constant set of values, that should be independent of the quantile, tau and that all of the variability arises due to beta. If I just fit the model using the quantreg package like so: mdl <- rq( y ~ alpha

Dear all, I am writing you for two problems I can not solve with R. I used both the 2.6.1 version and the 2.7.0 version. I run a sintax written by a collegue of mine, where there are involved both sparse matrix and quantile estimations. My data begins with 10008*14 observations and at maximum they reach 10008*834 observations. My questions are the following: first, when I give the command