similar to: logistic regression

hi all, I am fitting a logistic regression model on binary data. I care about the fitted probabilities, so I am not worried about infinite (or non-existent) MLEs. I use: > glm(Y~., data=X, weights=wgt, family=binomial(link=logit), maxit=250) I understand the three ways to fit model, and in my case Y is a factor, one column > Y <- c(rep("A",679), rep("B",38))

If I have a data frame where a species occupies several rows with different phases such as (both col's ar factors): species,phase Populus tremula,1 Populus tremula,2 Populus tremula,3 Calluna vulgaris,1 Calluna vulgaris,2 Betula alba,1 Betula alba,2 Betula alba,3 Primula veris,1 Primula veris,2 and another df where each species only have one row: species,growth_form Populus tremula,tree Acer

Hi Michael, A few comments 1. To add the constraint sum(wgt.vect=1) you would use the method of Lagrange multipliers. What this means is that in addition to the w_i (the components of the weight variables) you would add an additional variable, call it lambda. Then you would modify your optim.fun() function to add the term lambda * (sum(wgt.vect - 1) 2. Are you sure that you have defined

You can't -- at least as I read the docs for ?optim (but I'm pretty ignorant about this, so maybe there's a way to tweak it so you can). See here: https://cran.r-project.org/web/views/Optimization.html for other R optimization capabilities. Also, given your credentials, the r-sig-finance list might be a better place for you to post your query. Cheers, Bert Bert Gunter

Greetings Everybody: I generated a 1.2MB dta file based on the general social survey with Stata8 for linux. The file can be re-opened with Stata, but when I bring it into R, it says all the values are missing for most of the variables. This dataset is called "morgen.dta" and I dropped a copy online in case you are interested http://www.ku.edu/~pauljohn/R/morgen.dta looks like this

Hi ? This is giving me a headache. I?m trying to do a relatively simple optimization ? actually trying to approximate the output from the Excel Solver function but at roughly 1000x the speed. ? The optimization parameters look like this. The only trouble is that I want to add a constraint that sum(wgt.vect)=1, and I can?t figure out how to do that in optim. Mo.vect <-

Here is a runable program. When I plot Day and Wgt, it graphs all the data points. All I need is daily.sub1 plotted. I also need each "Tanks" to have its own col or pch. When I run it with the line with pch, it gives me nothing. rm(list=ls()) Trial<-rep(c(1,2),each=12) Tanks=rep(c("a3","a4","c4","h4"),each=3,2) Day=rep(c(1:12),2)

On Thu, May 3, 2018 at 2:03 PM, Michael Ashton <m.ashton at enduringinvestments.com> wrote: > Thanks Bert. But everyone on that forum wants to use finance tools rather than general optimization stuff! And I am not optimizing a traditional Markowitz mean-variance problem. Plus, smarter people here. :-) > I'm very confused by these statements. Most of the "finance tools"

Thanks Bert. But everyone on that forum wants to use finance tools rather than general optimization stuff! And I am not optimizing a traditional Markowitz mean-variance problem. Plus, smarter people here. :-) > On May 3, 2018, at 3:01 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > You can't -- at least as I read the docs for ?optim (but I'm pretty > ignorant

Is the code below showing a bug in Crosstable()? My expectation was that the values produced by xtabs were rounded instead of truncated: library(gmodels) abc <- c("a", "a", "b", "b", "c", "c") def <- c("d", "e", "f", "f", "d", "e") wgt <- c(0.8, 0.6, 0.4, 0.5, 1.4, 1.3)

OK, I need help plotting. I have column headings of Day, Wgt, Foodin, Rep, Grp and Tanks. Rep=c(1,2,3) and Tanks=c(a1,a2,a3,a4,a5,a6, c1,c2,c3,c4,c5,c6, h1,h2,h3,h4,h5,h6). I created a subset where I only would like Rep=2, and Tanks=c(a4,c4,h4) and would like to graph (points) of Wgt and Day. I would think that I only need 3 colors, but when I run with only 3, only 2 lines show up. When I add

Hi R-people: When I use the command to fit a model with an intercept, only: glm ( formula=haspdata ~ 1, data=dat, family=binomial, weights= dat$hy.wgt.s, subset=(dat$haspdat0!=3) ) I get the message: Warning message: non-integer #successes in a binomial glm! in: eval(expr, envir, enclos) Does anyone know what this means?? The data for this command is listed below. Thanks, Phil Smith CDC

hello, I am using LDA and QDA function of MASS library. I understand Fisher LDA is a method non-probabilistic in nature, so I wonder what happens when I try to predict my test set examples as in: > fit <- lda(labels~., data=train.table, prior=c(.5,.5)) > pred <- predict(fit, data=test.table, prior=c(.5,.5)) Specifically I ask this because in my problem there are 700 examples

Dear R users, I'm using the "reldist" add-on package to calculate relative distribution in R as part of my research project. The subject is a general mental health score ranging from 0 to 12 (integer values only) with 0 indicating no mental health problem and positive values meaning some or sever mental health problem. When I run the programme to compare the scores of population

> hi all, > I am using optim. I am getting the following error message: > > Error in optim(par = start.vals[, h], fn = post.func.pois, gr = post.grad. > pois, : > L-BFGS-B needs finite values of fn > > If I look at optim typing '> optim' it seems that the error comes from > inside .Internal(optim), so I wonder how can I see the code for .Internal(

I've noticed that R has a number of very useful functions for obtaining descriptive statistics on groups of variables, including summary {stats}, describe {Hmisc}, and describe {psych}, but none that I have found is able to provided weighted descriptives of subsets of a data set (ex. descriptives for both males and females for age, where accurate results require use of sampling

Hi I have a column of concatenated information stored in an RG object in the limma package and I need to split this information and then paste the first two pieces of data in each case back into two columns of the RG object. This is how I am currently doing this gene.info.split<-strsplit(RG$genes$Name,",",fixed=TRUE) for (h in 1: length(gene.info.split)){

hello all, I am trying to print a ps file as part of a function as in: func <- function (..., filename="temp.ps") { # some stuff [...] # plot eval( cat("postscript(\"",filename,"\")\n", sep="") ) plot(...) abline(...) dev.off() # more stuff [...] } but it does not work. Nor it does with 'paste' instead

Hello, I'm using the R package called mvpart, which is about the multivariate regression trees. The function I wrote is: mrt1<- mvpart(coefmat~sChip+sScreen+sMem,data=mixdata, xv="pick", plot.add=TRUE,uniform=TRUE,which=4,all=TRUE,xadj=2,yadj=2,rsq=TRUE,big.pts=TRUE,wgt.ave.pca=TRUE,legend=TRUE,bars=F, pca=TRUE) where "coefmat" is a matrix(of dimension N*K) to store

Hi, Thanks for answering my question on the new smbmount not working. I tried all variety of combinations on the commands you suggested, but they all simply do this: % smbmount -c //server/share 'mount /mnt/samba-share -n CLIENT -U user' Usage: smbmount service <password> [-p port] [-d debuglevel] [-l log] Version 2.0.3 -p port connect to the specified port