similar to: Unexpected behaviour of write.csv - read.csv

Hi, I hope some one can help. I need to compute Thurston's case 5 on a large set of data. I have gotten as far as computing the proportional preference matrix but the next math is beyond me. Here us my matrix 0.500 0.472 0.486 0.587 0.366 0.483 0.496 0.434 0.528 0.500 0.708 0.578 0.633 0.554 0.395 0.620 0.514 0.292 0.500 0.370 0.557 0.580 0.615 0.329 0.413 0.422 0.630 0.500 0.783 0.641 0.731

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474

Hi, In my analysis of impacts of insecticide-treated bednets on malaria, I look at the relationship between malaria incidence and mosquito behaviors. The condensed data set is copied here. Ordinary regression (lm) shows that Incidence was negatively related to Mortality. This makes sense because the latter reflected the strength of killing mosquitoes by insecticide-treated nets. Since the

Dear Thomas, The head of my dataset > head(wsuv) parcel sp time censo treatment species 1 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 2 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 3 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1 1 4 S8 Poecilanthe effusa ( Hub. ) Ducke. 1 1 1

Dear useRs, I am trying to model a time series with a transfer function. I think it can be put into the ARMA framework, and estimated with the 'arima' function (and others have made similar comments on this list). I have tried to do that, but the results have so far been disappointing. Maybe I am trying to make 'arima' do something it can't... The data are time series of

Dear all, I am attempting to explain patterns of arthropod family richness (count data) using a regression model. It seems to be able to do a pretty good job as an explanatory model (i.e. demonstrating relationships between dependent and independent variables), but it has systematic problems as a predictive model: It is biased high at low observed values of family richness and biased low at

OK, Let's try this again! Here is the reproducible script; it is long because I had to copy the panel dataset here. My question is related to systemfit; I don't know how to get the result for the entire panel. #Reproducible script Empdata<- read.csv("/Users/ngwinuiazenui/Documents/UPLOADemp.csv") View(Empdata) install.packages("systemfit")

I am installing R 2.15.1 onto RHEL 6, using gcc 4.7.0 with Intel MKL 10.3.7 and the following environment: export BLAS_LIBS="-Wl,--start-group /usr/caen/intel-12.1/mkl/lib/intel64/libmkl_gf_lp64.a /usr/caen/intel-12.1/mkl/lib/intel64/libmkl_sequential.a /usr/caen/intel-12.1/mkl/lib/intel64/libmkl_core.a -Wl,--end-group -lpthread" export LAPACK_LIBS="-Wl,--start-group

Hi Team, I downloaded the R 3.0.2 and, built and installed it using Intel compilers (icc and ifort) from Intel parallel studio 2013, sp1. After performing make tried to check it using 'make check'. Most of the tests passed successfully but while checking a 'stats' package I saw many lines were printed which did not match the desired output. e.g. There

Sadly you failed to set your email program to send plain text and the data is corrupted at my end. I also think you need to reduce the size of the data set... the intent here is to increase your understanding, not debug your particular analysis. I will say that I am having a very challenging time understanding what you are trying to accomplish though. What are the equations that you think need

Hello I am using R 2.2.0 with Windows XP. I've got a five element list object, each element containing two dataframes of equivalent size. > str(mylist) List of 1 $ data1:List of 2 ..$ data1a :`data.frame': 77 obs. of 63 variables: .. ..$ var1 : num [1:77] 0.41375 0.00056 1.43040 1.43528 0.61730 ... .. ..$ var2 : num [1:77] 1.154 1.686 0.673 0.800 0.760 ... ..

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter

Hi, I have the following file, and I need to work out the linear regression for each sample. I tried the model(*) and receive the error message (**): > data=split(mydata,rep(1:(nrow(mydata)/6),each=6)) > arrang.linear=lapply(data,lm,formula=KA~PA) Erro em storage.mode(y) <- "double" : invalid to change the storage mode of a factor Al?m disso: Warning message: In

Unless there is good reason not to, always cc the list -- there are lots of smarter folks than I on it who can help. I may or may not have time to look at this. Hopefully someone else will. -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip

Dear all I use aggregate with variables of type numeric and dates. For type numeric functions, such as sum() are very fast, but similar simple functions, such as min() are much slower for the variables of type 'dates'. The difference gets bigger the larger the 'id' var is - but see this sample code: dts <- dates(c("02/27/92", "02/27/92",

I have a file: x y z 0.025 0.025 1.65775 0.025 0.050 1.62602 0.025 0.075 1.63683 0.025 0.100 1.91847 0.025 0.125 2.00913 0.025 0.150 1.82222 0.025 0.175 1.70901 0.025 0.200 1.39759 0.025 0.225 1.39089 0.025 0.250 1.04762 If I read the file like this: data<-read.table("file.dat") How do I access the vectors x,y,z that are inside the dataframe data? I studied Venables and

Dear R help I am having difficulty doing a biplot of the first two factors of a factor analysis. I presume it is because the values in factor 2 for Milk and NUTS are not displayed in the component loadings. Loadings: Factor1 Factor2 RedMeat 0.561 -0.112 WhiteMeat 0.593 -0.432 Eggs 0.839 -0.195 Milk 0.679 Fish 0.300 0.951 Cereals -0.902 -0.267

I've written a very simple bit of code to plot a trajectory using rgl: x <- (c(0,-5.947,-11.496,-16.665,-21.474,-25.947,-30.116,-34.017,-37.684,-41.148,-44.435,-47.568,-50.567,-53.448,-56.223,-58.906)) y <- (c(0,33.729,65.198,94.514,121.784,147.151,170.797,192.920,213.717,233.360,252.003,269.774,286.781,303.117,318.858,334.071)) z <-

I am a total newbie at R but experienced with computers. If this is not the right forum for this question, please let me know one that is. I searched in the R manuals in the Help section, the Nabble help and Rseek but no luck. I am trying to install the package gcl on my recently installed R 2.8.1 I searched on cran for the windows version and found a zip file for the package In RGui, I ran

Dear list members, I apologize for putting this (probably) very basic question on the mailing list. I have scanned through the R website (using search) but did not found an answer. (code included below) A factor matrix is simply extracted (which can then subsequently be exported using write.table) by FACT$loadings[1:6,]. I would also like to specifically extract and export