similar to: how to the p-values or t-values from the lm's results

Hi all, I post it on both r-help and r-finance since I don't know where is most appropriate for this topic. Sorry if it bothers you. I did garch fitting on S&P500 monthly returns with garchFit from fSeries. I got same coefficients from all cond.dist except normal. I thought that is probabaly usual for the data. But when I play with it, I got another question. I plot skew normal with

The following behaviour (in R 0.62.3) is disturbing: > (0+0i)^2 [1] NaN+NaNi Is it deliberate?? Laimonis Kavalieris -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

The following behaviour (in R 0.62.3) is disturbing: > (0+0i)^2 [1] NaN+NaNi Is it deliberate?? Laimonis Kavalieris -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Hi. Background - I am working with a dataset involving around 750K observations, where many of the variables (8/11) are unordered factors. The typical model used to model this relationship in the literature has been a simple linear additive model, but this is rejected out of hand by the data. I was asked to model this via kernel methods, but first wanted to play with the parametric

Hello, I am new to non-linear growth modelling in R and I am trying to reproduce an analysis that was done (successfully) in S-Plus. I have a simple non-linear growth model, with no nesting. I have attempted to simplify the call as much as possible (by creating another grouped object, instead of using subset= and compacting the fixed and random expressions.) This is a what the grouped

Hello, I am trying to perform a logistic regression using counts. For example: cedegren <- read.table("http://www.cloudstat.org/index.php?do=/attachment/download/id_95 /", header=T) attach(cedegren) ced.del <- cbind(sDel, sNoDel) ced.logr <- glm(ced.del ~ cat + follows + factor(class), family=binomial("logit")) This works. However, if I change the family to

Dear All, I would like to be able to plot histograms/densities on a semi-log or log-log scale. I found several suggestions online http://tolstoy.newcastle.edu.au/R/help/05/09/12044.html https://stat.ethz.ch/pipermail/r-help/2002-June/022295.html http://www.harding.edu/fmccown/R/#histograms Now, consider the code snippet taken from http://www.harding.edu/fmccown/R/#histograms # Get a random

Hi List, I am looking for a variable selection procedure with a forward-backward selection method. Firstly, it is meant to work with the cophenetic correlation coefficient (CPCC) and intended to find the variable combination with the highest cophenetic correlation. Secondly, it is aimed at Gower metric with wards method (though this could be easily extended) aimed at categorical data. What I

Some of you may have seen the pythag() part in the R API definition in "Writing R Extensions" (source = doc/manual/R-exts.texinfo). or followed the report and Prof. Brian Ripley's answer about pythag()'s availability from R's binary. As we say in above manual >> `pythag(A, B)' computes `sqrt(A^2 + B^2)' without overflow or >> destructive

Simple example: # Classification Tree with rpart library(rpart) # grow tree fit <- rpart(Kyphosis ~ Age + Number + Start, method="class", data=kyphosis) Now I would like to know how can I measure the "importance" of each of my three explanatory variables (Age, Number, Start) in the model? If this was a regression model, I could have looked at p values from the

I don't understand the coefficients returned from the lm function. I expected these to be the mean values for each factor in the model. Given this data and model: data<-c(rnorm(10,mean=0,sd=1),rnorm(10,mean=1,sd=1),rnorm(10,mean=-.5,sd=1)) ftr<-as.factor(rep(1:3,each=10)) fit<-lm(data ~ ftr) the mean values of the three facotrs from the data: c(mean(data[1:10]),

Hi all, I was trying garchFIt() of fSeries to fit volatility of monthly log returns of S&P500. I tried residuals of normal, student t, skew normal, skew t. But all innovations except normal got exaxtly same coefficients, even if I changed their parameters of skew and shape. Is this correct for the data or something wrong? I am attaching the code, thank you. Muster #GARCH analysis of

I would like to call both p-values and R-squared values from lm's in a function. I can get the p-values from coef(summary(name.lm))[r,c], however, I cannot figure out how to call the R-squared values without manually calling the summary and inserting them in the script - which negates the value of automating the process through a function. Thanks, Mike [[alternative HTML version deleted]]

Dear Colleagues, I run this model: mod1 <- lmer(x~category+subcomp+category*subcomp+(1|id),data=impchiefsrm) obtain this summary result: Linear mixed-effects model fit by REML Formula: x ~ category + subcomp + category * subcomp + (1 | id) Data: impchiefsrm AIC BIC logLik MLdeviance REMLdeviance 4102 4670 -1954 3665 3908 Random effects: Groups Name Variance

Hello, I have a deriv function that I am feeding to nlme. It works, and I can use it in nls, but when I try to use it in nlme I get Error: subscript out of bounds. I can fit the model using SSasympOrig, instead of the deriv function, but I am trying to reproduce an earlier analysis (done in Splus) and I get slightly different results with SSasympOrig. Here are my calls: This does fit

I am using psm to model some parametric survival data, the data is for length of stay in an emergency department. There are several ways a patient's stay in the emergency department can end (discharge, admit, etc..) so I am looking at modeling the effects of several covariates on the various outcomes. Initially I am trying to fit a survival model for each type of outcome using the psm

The blowfish crypt(3) mechanism supports the use of a "cost value" for password encryption. The cost value is encoded into the encrypted password that is stored in master.passwd. On OpenBSD, this cost value can be set in login.conf. FreeBSD does not currently support the cost value. The cost value is the base-2 logarithm of the number of rounds of encryption to use so

Is there an easy way to display the SQL in script/console (similar to what is done in development.log)? The following works but it''s ugly: $ script/console Loading development environment. >> class ActiveRecord::ConnectionAdapters::AbstractAdapter >> def logger= (logr) >> @logger = logr >> end >> end => nil >>

Hi all, I use XP on my laptop PC, with 30 GB HD (single partition), and a 3.5" hard drive (not a stick), accessed through a USB encasing, partitioned as five logical drives. I have successfully set up syslinux to boot several Ubuntu versions from the primary USB hard drive partition, and no problems there. The problem is, I would like to have an entry in the menu, like "Boot from

Hello, I have attached a model file which can be used to rank new queries. Disclaimer: I don't remember if its is the updated one or the one with which I evaluated the API before. But it should work with your new queries with libsvm based letor module. Parth. -------------- next part -------------- An HTML attachment was scrubbed... URL: