similar to: Subject: Regress multiple independent variables on multiple dependent variables

On 2011-01-27 14:22, Rasti Matus wrote: > I have a few questions regarding machine learning packages in R, > e.g. earth package ... > > 1) How could I force the algorithm to generate knots only with > values < 90 for variable doy? Not possible in the current implementation. In principle it would be possible to extend earth so the user-defined "allowed" function

Hi, I have a few questions regarding machine learning packages in R, e.g. earth package and its forward pass and prunning pass, and hinge functions selection in the example below. 1) How could I force the algorithm to generate knots in hinge function only with values < 90 for e.g. variable doy? 2) Is it possible to restrict the algorithm to generate maximum number of terms per a selected

Dear All, I?m using lme to analyze a time series gene expression data. I don?t have all animals in all times, the number of animals in each time is different and I have lots of NA values. An example file can be downloaded at lbmp.fcav.unesp.br/leonardo and the code used is the following: teste<-read.table(file='example.csv',sep=',',header=T) B<-1366 library(nlme)

On Jun 22, 2011, at 6:15 PM, Jim Grosbach wrote: > > On Jun 22, 2011, at 9:00 AM, Renato Golin wrote: > >> On 22 June 2011 16:50, Jim Grosbach <grosbach at apple.com> wrote: >>>> This sounds like a dead end as newer binutils are GPLv3. >>> >>> Yeah, that's definitely a very real concern and a big motivation to get the MC based asm parser

Hello. Can anyone please take a second to help me out with this problem? I try to run Longman iBT 2.0 Toefl with the last version of Wine / Lubuntu / FGLRX (video driver for ATI HD 4330 ) / Java. I have the last version of all these... As you can see, the program runs but some items are not displayed or wrong displayed. Moving the pointer or moving the window can make the image better or worse.

Linux GABI [1] introduced new .note.gnu.property section which contains a program property note which describes special handling requirements for linker and run-time loader. LLD does not support .note.gnu.property yet. GABI specifies 2 types of entries: GNU_PROPERTY_STACK_SIZE and GNU_PROPERTY_NO_COPY_ON_PROTECTED: * GNU_PROPERTY_STACK_SIZE: Its pr_data field contains an integer in the format

I think we should wait until there is someone wanting to use these features with lld. Cheers, Rafael ‐‐‐‐‐‐‐ Original Message ‐‐‐‐‐‐‐ On March 20, 2018 6:59 AM, George Rimar <grimar at accesssoftek.com> wrote: > Linux GABI [1] introduced new .note.gnu.property section which contains a program > property note which describes special handling requirements for linker and run-time

New installation seems to have behavior I cannot figure out. Here is illustrative sequence where I load a small data set (test) from Crawley's files and try to run a simple linear model and get an error message. Oddly, R reports that the variable 'test$ozone' is numeric while, after attaching test, the variable ozone is not numeric. Can someone please help? This behavior is

> library(reshape2) > x = melt(airquality, id=c('month', 'day')) With reshape I can cast with multiple functions: > library(reshape) > cast(x, month+variable~., c(mean,sd)) month variable mean sd 1 5 ozone 23.615385 22.224449 2 5 solar.r 181.296296 115.075499 3 5 wind 11.622581 3.531450 4 5 temp 65.548387

I think I've gotten my Emacs/Sweave/R system set up correctly, thanks to Vincent and Jim, but I haven't been successful getting my first document produced. I'm trying to use one of Friedrich Leisch's examples, http://www.ci.tuwien.ac.at/~leisch/Sweave/example-1.Snw. I cut and pasted the text into a document sweaveexample.Rnw in Emacs. It seemed to be processed successfully with R:

Hello Given the following data for a data set called airquality. To identify the nature of the objects from the data set airquality example "Ozone" would it be best to use the command is. like is.character(airquality$Ozone) ....... I tried attributes(airquality$Ozone) but it came up null. Would there be a better way to identify these objects. Thanking you in advance for your

Hi Gustav, Try this: lapply(1:length(models),function(i) lapply(models[[i]],function(x) summary(x)$coef[2,]))[[1]] #1st list component [[1]] #??? Estimate?? Std. Error????? z value???? Pr(>|z|) # pm10 #5.999185e-04 1.486195e-04 4.036606e+00 5.423004e-05 #[[2]] #??? Estimate?? Std. Error????? z value???? Pr(>|z|) #ozone #0.0010117294 0.0003792739 2.6675428048 0.0076408155 #[[3]] #???

>>>>> peter dalgaard <pdalgd at gmail.com> >>>>> on Mon, 26 Jun 2017 13:43:28 +0200 writes: > This seems to be due to changes made by Martin Maechler in > 2008. Presumably this fixed something, but it escapes my > memory. Yes: The change set (svn -c46441) also contains the following NEWS entry BUG FIXES o

I hope my problem is not too basic to post here. I am a beginner having problems with some matrix manipulation. The data I am working with are sites with hourly ozone readings and is in a matrix where each row is a site and each column is an hourly reading. So for 10 sites, one day's worth of data is a 10x24 matrix - column 1 is the ozone measurement for midnight GMT, column 2 is ozone at

R-help, I'm using the "update" command for a multiple regression model and it is just not working: > update(model1, . ~ . – temp:wind:rad,data=ozone.pollution) Error: unexpected input in "model2<-update(model1, . ~ . –" > summary(model1) Call: lm(formula = ozone ~ temp * wind * rad + I(rad^2) + I(temp^2) + I(wind^2), data = ozone.pollution) Residuals:

Hi just a quick inquiry Sorry if this is too trivial but I am just a beginner in R. I am looking at the plyr package and I am intrigued at how data(i.e. ozone, baseball) is loaded without having to type data(ozone). Are they automatically loaded when i call library(plyr)? I want to do the same thing when I make my package. How does one accomplish this? Also, are there any beginner guides on how

I want to 1) Select for each of the n points in a matrix A, those of the m points in B that lay within a given radius. 2) Of those points within the radius, select the k nearest ones. What I now do is 1) Create an n*m matrix C were I put the distances from all the points in B to the points in A and make NA those cells were the distance is larger than the radius. (The points are geographical

Gracias a los tres, Raúl, Marcelino y Carlos. Lo del "get" de Marcelino me da la respuesta a lo que yo exactamente preguntaba, y funciona, pero ahora tengo problemas con el for, por lo que probablemente recurra al eval parse de Raúl o Carlos, que ya tienen el for. Aún así, lo intento 1º con el get. Con subset(df, subset=get(GT[i])>0) el problema es que en el for hago un

Hi all, We are facing a problem while introducing ourselves to Reshape package use. Melt seems to work fine, but cast fails when we use mean as fun.aggregate. As you see here, length and sum work fine, but mean throws this same error whatever dataset we use. > cast(aqm, month ~ variable, length) month ozone solar.r wind temp 1 5 26 27 31 31 2 6 9 30 30

Hi All, I've reproduced the example from Prof. Friedrich Leisch's webpage. When I write sweave("Example-1.Snw") OR sweave("Example-1.Rnw"), (yes, I renamed them). I get the following error: Writing to file example-1.tex Processing code chunks ... 1 : echo term verbatim Error: chunk 1 Error in library(ctest) : there is no package called 'ctest' Also while