similar to: Help with apply

I am using both nlminb and optim to get MLEs from a likelihood function I have developed. AFAIK, the model I has not been previously used in this way and so I am struggling a bit to unit test my code since I don't have another data set to compare this kind of estimation to. The likelihood I have is (in tex below) \begin{equation} \label{eqn:marginal} L(\beta) = \prod_{s=1}^N \int

I have constructed the function mml2 (below) based on the likelihood function described in the minimal latex I have pasted below for anyone who wants to look at it. This function finds parameter estimates for a basic Rasch (IRT) model. Using the function without the gradient, using either nlminb or optim returns the correct parameter estimates and, in the case of optim, the correct standard

Does anyone see why my code does not integrate to 1? library(statmod) mu <- 0 s <- 1 Q <- 5 qq <- gauss.quad(Q, kind='hermite') sum((1/(s*sqrt(2*pi))) * exp(-((qq$nodes-mu)^2/(2*s^2))) * qq$weights) ### This does what's it is supposed to myNorm <- function(theta) (1/(s*sqrt(2*pi))) * exp(-((theta-mu)^2/(2*s^2))) integrate(myNorm, -Inf, Inf)

Dear R-Users, I have a problem on extracting T-Stat and P-Value. I have written R-code below library("Matching") data("lalonde") attach(lalonde) names(lalonde) Y <- lalonde$re78 Tr <- lalonde$treat glm1 <- glm(Tr~age+educ+black+hisp+married+nodegr+re74+re75,family=binomial,data=lalonde) pscore.predicted <- predict(glm1) rr1 <-

Hi R-users,  I have a data from multi skew t and would like to transform each of the data to uniform data.  I tried using 'pmst' but only got one output:   > rr1 <- as.vector(r1);rr1  [1]  0.7207582  5.2250906  1.7422237  0.5677233  0.7473555 -0.6020626 -2.1947872 -1.1128313 -0.6587316 -1.1409261     > pmst(rr1, xi=rep(0,10), Omega=diag(10), alpha=rep(1,10), df=5) [1] 3.676525e-09

Hi R-users: [R 2.2 on OSX 10.4.3] I have a (sparse) vegetation data frame with 500 rows (sampling units) and 177 columns (plant species) where the data represent % cover. I need to summarize the cover data by returning the names of the most dominant and the second most dominant species per plot. I reduced the data frame to omit cover below 5%; this is what it looks like stacked. I have

Dear r-users, I would like to convert my Matlab code to R-code, however it dies not work as expected.  Hope somebody can help me to match Matlab and r codes. R code: rr <- function(r,cxn) { tol <- 1E-4; for(i in 1:n) { t1 <- (1+(i-1)*r)*log((1+(i-1)*r)) t2 <- (i-1)*(1-r)*log(1-r) rri <- ((t1+t2)/i*log(i))-cxn rr <- rri > tol } round(rr,4) } rr1 <- rr(0.5,0.0242) ; rr1

I have the following code which produces the output below it clus1 <- svydesign(ids = ~schid, data = lower_dat) items <- as.formula(paste(" ~ ", paste(lset, collapse= "+"))) rr1 <- svymean(items, clus1, deff='replace', na.rm=TRUE) > rr1 mean SE DEff W525209 0.719748 0.015606 2.4932 W525223 0.508228 0.027570 6.2802 W525035 0.827202

(summary.default): show the vector length in addition to quantiles diff -u -i -p -F '^(def' -b -w -B /home/sds/src/R-3.0.1/src/library/base/R/summary.R.old /home/sds/src/R-3.0.1/src/library/base/R/summary.R --- /home/sds/src/R-3.0.1/src/library/base/R/summary.R.old 2013-03-05 18:02:33.000000000 -0500 +++ /home/sds/src/R-3.0.1/src/library/base/R/summary.R 2013-09-10 10:19:02.682946339

Dears, My samba version is 3.6.4 I have a problem to co-work with open LDAP server. When samba join to open LDAP server, my local account can NOT login samba anymore, only LDAP account can login. When my samba come back to standalone, the local account is OK. Did I miss something? The following is my configuration files, I list the part of them, smb.conf server string = "Samba Server"

Hello, eveRybody, I've been trying to find the origin for the following formatting-"inconsistency": E. g., look at the number of digits in summary.defaults()'s output when NAs occur: in my example below the number of NA's is displayed as an integer, the rest as numeric (floating point numbers): > summary.default( c( 1:2, NA)) Min. 1st Qu. Median Mean 3rd Qu.

nchar(with(list(2),ls())) gives an internal error. This is of course a peculiar call (no names in the list), but the error is not caught cleanly. It is not clear from the documentation whether with(list(2)...) is allowable; if it is not, it should presumably give an error. If it is, then ls shouldn't have problems with the resulting environment. > qq <- with(list(2),ls())

I got QQ International (version 1.0) to work via WINE under Mepis 8.5. Using winetricks, I installed all of the missing DLL's, and QQ now starts up and runs fine. ... except for the fact that it always shows me as being "Away". Even if I manually set my status to "Online", it changes me back to "Away" after a second or two. This only happens under WINE. I log in

Hello, I am having two data set original and predicted. I want to dind QQ-plot fot it. I tried in following manner : >qq(original~predicted) and error was : Error in qq.formula(o ~ p) : y must have exactly 2 levels There is an option "qtype" which dosent make any difference. What is the correct way for plotting QQ-plot or am I missing something. -- Amar Kumar Nandan

Hello, I am in the process of writing a Perl program to carry out and analyze large numbers of regressions using R as the regression engine, and I am using Statistics::R to create the communication bridge between the two programs. Statistics::R creates a pipe between R and Perl and uses Rterm.exe (hidden during run-time) to carry out the R commands. This communication bridge works well for

This may not be the smoothest way to produce the result, but here is a two-step solution: first find the formula within the object created by the call to glm(): form <- qq["formula"] or equivalently form <- qq$formula then apply the function all.vars() to the result, and return the first element variables.in.formula <- all.vars(form) variables.in.formula[1] # will be the

As I mentioned in the subject, I have installed the latest version of QQ International (beta 3), under wine in ubuntu lucid. It installs without much trouble, however when I run the application, nothing happens. How do I begin troubleshooting this application to see if I can make it work? Or if anyone happens to know of an x64 linux qq client that actually works that would be great too :D

I can't get switch() to work as expected with the letter 'E'. The following example from help works just fine. > ccc <- c("b","QQ","a","A","bb") > for(ch in ccc) cat(ch,":",switch(ch, a=1, b=2:3), "\n") b : 2 3 QQ : a : 1 A : bb : Now I replace "a=1" with "E=1"

Full_Name: Jarno Tuimala Version: 1.5.0 OS: Windows Nt Submission from: (NULL) (193.166.1.21) Running the following analysis gives as a result kukot vs. kisut. aikaero <- -27.5+5*(0:10) frekvenssi.m <- c(0,1,15,37,53,45,23,18,4,1,1) frekvenssi.n <- c(2,8,12,19,33,47,42,15,2,1,0) win.graph() aikaero <- rep(c(aikaero,aikaero), c(frekvenssi.m,frekvenssi.n)) a.ero <-

I'm new to R (and to S) and am wondering about code from pages 72 and 83 of MASS (Venables+Ripley, 3rd edition), to draw an envelope on a QQ plot. Copying from the book, I've got: #... code whose gist is "a.fit <- nls(..." num.points <- length(resid(a.fit)) qqnorm(residuals(a.fit)) # illustrate data-model residuals qqline(residuals(a.fit)) samp <-