similar to: Forcing standard notation in Sweave tables

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Hello, I'm a new user to R so apologies if this is a basic question, but after scouring the web on information for summary.formula, I still am searching for an answer. I made a function to analyze my data - I have a categorical variable and three continuous variables. I am analyzing my continuous variables on the basis of my categorical variables. radioanal <- function(a) { #Educational

Dear all, I did post this more or less identical mail in a follow up to another question I posted, but under another heading. I try again, but now under the correct header. upon running this code (from the Hmisc library-latex function) I believe the call to summary.formula is allright and produces wonderful tables, but the latex command results in a correct formatted table but where all the

Dear Users, Still having troubles with sharing my results, I'm trying to display a contingency table using summary.formula. Computing works well but I'd like to display information on redundant entries say, males AND females. I wonder if this code is correct : desqualjum <- summary.formula(varqual1$X ~., data = subset( varqual1, select = -X), method = "reverse", overall =

Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add

I have one factor with say five levels (fact) of different size and a corresponding variable (var). I randomly generate five new levels (nfact ex. 2,2,1,5,4). What I would like to do is to extract the corresponding variable values into a new variable (nvar). I did try the following, why doesn't it work? nvar<-var[fact==nfact[ ]] Patrik Waldmann

I have seen two main styles in examples for using rsync with exclude-from. The first is simply a list of filename, one per line. The second is a list of filenames, one per line, prefixed with either a - or a + to indicate exclude/include. Which is correct? Also, none show the correct style with a filname containing spaces, though I assumed quoting is OK Exclude1.txt: - filename1 - ?file name

I dont get it: > is.vector(c(mydf[1])) [1] TRUE > unique(c(mydf[1])) Error in unique(c(mydf[1])) : unique() applies only to vectors > Is it a vector or not? This stuff is driving me nuts. I'm simply trying to convince R that my grouping vector is actually a vector so that unique will work. Its just a vector of numbers, so why shouldnt it work? --

I am trying to get summary statistics from WinBUGS/JAGS output in the form of mcmc.list objects, using the summary() function. However, I get odd warning messages: Warning messages: 1: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : algorithm did not converge 2: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : algorithm did

Can one perform a QDA in R? I do not see it anywhere within the mda package. Any pointers here would be appreciated. Thanks, cjf -- ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~* Christopher J. Fonnesbeck Ph.D. Student Georgia Cooperative Wildlife Unit University of Georgia Athens, GA 30602 Email: cjf at fonnesbeck.net Yahoo: fonnesbeck_chris ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*

Hello, I am trying to import a list of "structure" objects into R (data for BUGS, actually), but am having little success. In the help file for scan there dies not seem to be a list of valid values for the "what" keyword. Can anyone provide me with one? I have pasted in a sample input file that I am trying to import below this message. I have tried

Hi everybody, I'm trying to fit a Garch(1,1) process to the DAX returns. My data consists of about 2300 10day-logreturns in chronologically descending order (see attachment). But if I use the garch function I get a very high alpha_1 and a quite low beta, which doesn't make that much sense. I think I am missing something, but have no idea what it might be. I'd appreciate it a lot

Several updates have been made to the Hmisc package: Changes in version 3.16-0 (2015-04-25) * html.contents.data.frame: corrected html space character to add semicolon * ggplot.summaryP: added size of points according to denominators * colorFacet: new function * labelPlotmath: added chexpr argument (used by rms::ggplot.Predict) * rcsplineFunction: added

Several updates have been made to the Hmisc package: Changes in version 3.16-0 (2015-04-25) * html.contents.data.frame: corrected html space character to add semicolon * ggplot.summaryP: added size of points according to denominators * colorFacet: new function * labelPlotmath: added chexpr argument (used by rms::ggplot.Predict) * rcsplineFunction: added

I was wondering if there is a way of predicting factor scores of new data for factor analysis in R (similar to "predict" in S-plus). So far I have not been able to find it, nor found reference to it. Thanks, Chris Fonnesbeck -- ~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~*~* Christopher J. Fonnesbeck Ph.D. Student Georgia Cooperative Wildlife Unit University of Georgia Athens, GA 30602

I am trying to build 1.6.2 from source RPM's on RedHat 9, but encounter a failure when running the base tests. An inspection of base-Ex.Rout.fail reveals the following: > ##___ Examples ___: > > var(1:10)# 9.166667 [1] 9.166667 > > var(1:5,1:5)# 2.5 [1] 2.5 > > ## Two simple vectors > cor(1:10,2:11)# == 1 [1] 1 > > > stopifnot( is.na(var(1)), +

I noticed in the collection of contributed packages for the OSX release of R, there is no RMySQL package. Does anyone know if one exists, or otherwise, how to connect to relational databases from R on Mac? Any help mode appreciated. cjf

Howdy I apologize for duplicated posting. But I decided to correct my previous posting. I had the regression results using r <- lm(Y ~ nemp + as.factor(devt), data=d). First, there is the result of anova(r). Here I could not find regression coefficients. Response: Y Df Sum Sq Mean Sq F value Pr(>F) nemp 1 58.2 58.2 1233.23 < 2e-16 ***

Hmisc 4.0-0 is now on CRAN. The package has undergone a massive update. The most user-visable changes are; - support for Rmarkdown html notebooks - advanced html tables using the htmlTable package and summaryM function; can copy and paste into word processors - support for plotly interactive graphics, e.g. options(grType='plotly') plot(describe(mydata)) - new function

Hmisc 4.0-0 is now on CRAN. The package has undergone a massive update. The most user-visable changes are; - support for Rmarkdown html notebooks - advanced html tables using the htmlTable package and summaryM function; can copy and paste into word processors - support for plotly interactive graphics, e.g. options(grType='plotly') plot(describe(mydata)) - new function