search for: irls

...the weights used in the IWLS process wresid a working residual, weighted for "inv.var" weights only. How to use these input arguments? Anybody please shed some light? Also, is my understanding below correct? The input argument "w" is used for the initial values of the rlm IRLS weighting and the output value "w" is the converged "w". The "weights" input argument is actually what I want to apply - if I have my own set of weights. And the real/actual weights are the product of "weights"(I supplied) and the converged output "w&qu...

Hi, In the help files in the ?mgcv package for the gam.control() function, there is an option irls.reg. The help files describe this option as: For most models this should be 0. The iteratively re-weighted least squares method by which GAMs are fitted can fail to converge in some circumstances. For example, data with many zeroes can cause problems in a model with a log link, because a mean of z...

I set up printing IAW: http://us4.samba.org/samba/docs/man/printing.html I've confirmed the drivers are being installed to /etc/samba/drivers/W32X86. Yet I am unable to print even a test page. I get the following error: "Test page failed to print. Would you like to view the print trouble shooter for assistance? Access is denied." And I get the following errors in my samba

Hello all, I've gotten the printing subsytem almost working - I think. I am able to install my print drivers to the server IAW the instructions found here: http://us4.samba.org/samba/docs/man/printing.html The drivers are being installed to /etc/samba/drivers/W32X86 IAW /etc/samba/smb.conf by following the instructions above This line specifically seems to do it: [print$] path =

Hi! I've got FreeBSD 8.3-STABLE/i386 server that can be reliably panicked using just 'squid -k rotatelog' command. It seems the system suffers from the problem described here: http://cxsecurity.com/issue/WLB-2010090156 I could not find any FreeBSD Security Advisory containing a fix. My server has 4G physical RAM (about 3.2G available) and runs squid (about 110M VSS) with 500

Here in Sweden, it's supposed to be springtime. A wonderful time of the year, with sunny skies and wonderful weather. Almost summer. Today, it's not. It's winter all over again with rain and only 3 degrees celsius outside. Better to stay inside and write a weekly Asterisk newsletter :-) This week's topics: ------------------- * Looking beyond Asterisk 1.0/1.1 - what's up? *

Dear R developers, I have noticed a discrepancy between the coefficients returned by R's glm() for logistic regression and SAS's PROC LOGISTIC. I am using dist = binomial and link = logit for both R and SAS. I believe R uses IRLS whereas SAS uses Fisher's scoring, but the difference is something like 100 SE on the intercept. What accounts for such a huge difference? Thank you for your time. Ben Godlove [[alternative HTML version deleted]]

The text below is a part of, some work I have to do, which is due in 2 days and I am strung up with a lot of other stuff, so I was hoping someone would take 5 mins and help me ?? Here is a part of my data.frame: year country1 country2 contig comlang pop1 gdp1 pop2 gdp2 rta dist avgflow 1 1992 AUS AUT 0 0 17.4950008 321708.281

Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico

hi everyone, This mail will mostly interest europeans Rubyists/Railists, but others are welcome to read it, answer and participate too :) In next February the Sixth Fosdem (Free and OpenSource Developers'' European Meeting) will be held in Brussels, Belgium. Like each year there is some special rooms for projects/communities (mozilla, drupal, kde, gnome, python, openbsd, perl, linux,

...stoph Lehman had problems with seperated data in two-class logistic regression. One useful little trick is to penalize the logistic regression using a quadratic penalty on the coefficients. I am sure there are functions in the R contributed libraries to do this; otherwise it is easy to achieve via IRLS using ridge regressions. Then even though the data are separated, the penalized log-likelihood has a unique maximum. One intriguing feature is that as the penalty parameter goes to zero, the solution converges to the SVM solution - i.e. the optimal separating hyperplane see http://www-stat.stanf...

...l using family=poisson(link = "identity"). The problem is that the glm function fits a model with a negative intercept, which sounds like a nonsense to me, being the response a Poisson variable. >From a previous discussion on this list I've understood that the glm function uses IRLS for the fitting without any constraint so it is possible for it to end up in a region of values which are not admissible given the model, and in fact sometimes it fails asking for valid starting values. In this case I expected it to fail asking to supply starting values, and instead it fits the...

Hi, I am trying to build GAM with linear constraints, for a general link function, not only identity. If I understand it correctly, the function pcls() can solve the problem, if the smoothness penalties are given. What I need is to incorporate the constraints before calculating the penalties. Can this be done in R? Any help would be greately appreciated. -- View this message in context:

Is anyone else concerned with the way in which the R function parser relocates comments that occur after condional expressions in functions to before, i.e. fred <- function(x) { # wonder what x is like if (x>0) stop("Sorry non-positive x only") # that showed x big-time! x } but then fred is parsed and stored as "fred" <- function (x) { # wonder what x is

I have written a program to solve a particular logistic regression problem using IRLS. In one step, I need to integrate something out of the linear predictor. The way I'm doing it now is within a loop and it is as you would expect slow to process, especially inside an iterative algorithm. I'm hoping there is a way this can be vectorized, but I have not found it so far. The...

...ssage: " There were 12 warnings (use warnings() to see them)" So I checked them: Warnings 1 to 11 said: 1: optim returned message ERROR: ABNORMAL_TERMINATION_IN_LNSRCH in: "LMEoptimize<-"(`*tmp*`, value = structure(list(maxIter = 50, ... and Warning 12 said: 12: IRLS iterations for glmm did not converge in: lmer(Enfermo ~ Bloque + Trat * Var * dia + (1 | IDfruto), data = desinf, ... There was no error message in the call of lmer function, so: What do these warnings mean? Do these errors occur at earlier iterations but finally the model converges? Can th...

Dear All, I have the following error message when I fitted lmer to a binary data with the "AGQ" option: Error in family$mu.eta(eta) : NAs are not allowed in subscripted assignments In addition: Warning message: IRLS iterations for PQL did not converge Any help? Thanks in advance, Abderrahim [[alternative HTML version deleted]]

Hi all! My question is why, and what I can do about that I sometimes, but not always, get warning-messages like nlminb returned message singular convergence (7) in: LMEopt(x = mer, value = cv) or IRLS iterations for PQL did not converge when trying to fit a model looking like this: lmer<-(cbind(Diseased,Healthy)~Fungus+(1|Family)+(1|Fungus:Family), family="binomial") to four similar data sets? All four data sets consists of four columns; Fungus (1 or 2), Family (1-30), Diseased...

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Dear R users, I use the glm() function to fit a generalized linear model with gamma distribution function and log link. I have read in the help page that the default method used by R is "glm.fit" (iteratively reweighted least squares, IWLS). Is it possible to use maximum likelihood method? Thanks Silvia Narduzzi Dipartimento di Epidemiologia ASL RM E Via di S. Costanza, 53 00198