similar to: lookup in CSV recipe

Hi I would like to shorten mod1 <- nls(ColName2 ~ ColName1, data = table, ...) mod2 <- nls(ColName3 ~ ColName1, data = table, ...) mod3 <- nls(ColName4 ~ ColName1, data = table, ...) ... is there something like cols = c(ColName2,ColName3,ColName4,...) for i in ... mod[i-1] <- nls(ColName[i] ~ ColName1, data = table, ...) I am looking forward to help Christof

Hi all R users Ive got a file that contains diffrent settings in the manor of: setting1="value1" setting2="value2" setting3="value3" setting4="value4" . . . What I want to do is open the file and change the value of a specific setting like wanna change setting4="value4" -> setting4="value5" and then save the file again.

I would write in tab-text file a table like this one: TAB colname1 TAB colname2 TAB TAB... colnameN rowname1 # # # rowname2 # # # rownameM # # # then I wrote something like: mymatrix <- matrix(nrow=M,ncol=N,byrow=T) rownames(mymatrix) <- chvector1 colnames(mymatrix) <- chvector2

Hello, In doing a series of non-linear estimations of a function which is a sum of a varying number of sinusoids, I would like to "autogenerate" the arguments needed by nls() depending on that number. For example, when there are two sinusoids: > nls( y ~ mu + A1 * cos(2*pi*f1*x - P1) + A2 * cos(2*pi*f2*x - P2), data = some.xy.data, start = list( mu=some.value0,

Dear R-users, is there some way how to pass various colnames to the following code for sorting data.frames? mydf.ordered<-with(mydf, mydf[order(colname1,colname2, colnameX, decreasing = TRUE), ]) I was trying something like Afunction<-function (mydf,colnames,decreasing=T){ mydf.ordered<-with(mydf, mydf[order(colnames, decreasing = decreasing), ]) } but it didnt work please

Hello, The code below is supposed to be a wrapper for matplot to do columnwise visible comparison of several matrices, but I'm doing something wrong because I can't access an argument called 'colnum'. I'd be most grateful for some insight. Thanks, John Thaden Little Rock, AR ################################ # mmatplot is a matplot wrapper to compare the same column of #

Hello, I'm using a very large data set (n > 100,000 for 7 columns), for which I'm pretty happy dealing with pairwise-deleted correlations to populate my correlation table. E.g., a <- cor(cbind(col1, col2, col3),use="pairwise.complete.obs") ...however, I am interested in the number of cases used to compute each cell of the correlation table. I am unable to find such a

>I have a series of write statements because >i am writing to a file >where the characters strings are the column names of a dataframe >and the numbers are the elements in a particular row. >So, a file might look like > >AAA 2.1 >BB 3.1 >AHLZ 0.2 > >and it would be named "rowname".mls. > >so, each time i get to a new row, i create a new file and

Please help me solve the following error message: syntax error, unexpected tINTEGER, expecting $end I have this model: Code: 1. class GeoDatum < ActiveRecord::Base 2. end The database contains the table geo_data, which contains the zip_code column, filled with zip codes. I get the above error when searching for a zip code and the zip code exists in the table. Here is the

Hi all, This is a very basic question, but I just can't figure out why R is handling a loop I'm writing the way it is. Here is the script I have written: grid_2_series<-function(gage_handle,data_type,filename) series_name<-paste(gage_handle,data_type,sep="_") data_grid<-read.table(file=paste(filename,".txt",sep=""))

Hi list, Could you explain the error I see here? Thanks! ## I'm using R 2.8.0 on WinXP, Hmisc_3.4-3 > table1 <- matrix(10, 180,7) > cell.format <- matrix("", ncol=7, nrow=180) > cell.format[c(seq(3,180,6),seq(4,180,6)),] <- "color{red}" > cell.format[c(seq(5,180,6),seq(6,180,6)),] <- "color{green}" > > latex(table1,

I have a site on a shared host at TextDrive. I have an import process that imports a CSV file into the database using a ruby script executed using script/runner. TextDrive has a memory limit which I am hitting and the process gets killed. I get through to about 400 records before it dies. I guess each time I instantate a new object for each record I am using more memory but thought I was using

Hello Lets say as an example I have a dataframe with the following attributes: rownum(1:405), colnum(1:287), year(2000:2009), daily(rownum x colnum x year) and foragePotential (0:1, by 0.01). The data is actually stored in a netcdf file and I'm trying to provide a conceptual version of the data. Ok. I need to calculate a moving mean and a moving variance for each cell on the following

Simple problem but I don't see the answer. I'm trying to clean up some data I have 120 columns in a data.frame. I have one value in a column named "blaw" that I want to change. How do I find the coordinates. I can find the row by doing a subset on the data.frame but how do I find out here "blaw " is in columns without manually counting them or converting names(Df) to a

Dear R gurus, I have the following code, but I still not know how to estimate and extract confidence intervals (95%CI) from resampling. Thanks! ~Adriana #data penta<-c(770,729,640,486,450,410,400,340,306,283,278,260,253,242,240,229,201,198,190,186,180,170,168,151,150,148,147,125,117,110,107,104,85,83,80,74,70,66,54,46,45,43,40,38,10) x<-log(penta+1) plot(ecdf(x),

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I'd like to be able to colour histograms along the diagonal using the colours stored in colnames(d): > d black blue brown cyan 1 0.96405751 -0.02964390 -0.060147424 -0.06460070 2 -0.03614607 0.95475444 -0.152382053 -0.07767974 3 -0.07095613 -0.05884884 -0.061289399 -0.06445973 4 -0.03708223 -0.05997624

I have a bunch of data sets that were created for the libsvm tool. They are in "colon separated sparse format". i.e. 1 5:1 27:3 345:10 Is a row with the label of "1" and only has values in columns 5, 27, and 345. I want to read these into a data.frame in R. Is there a simple way to do this? -- Noah Silverman, M.S. UCLA Department of Statistics 8117 Math Sciences

Hi! Thanks for the replies! I understand people more accustomed to R doesn't like looping much, and that thinking about loops is something I do since I worked with Stata a lot. The syntax from Peter Dalgaard was really clever, and I learned a lot from it, even though it didn't solve my problem (I guess it wasn't very well explained). My problem was basically that I have a data matrix

Dear R users, suppose I have a matrix of observations for which I calculate all pair-wise correlations: m=matrix(sample(1:100,replace=T),10,10) w=cor(m,use="pairwise.complete.obs") How do I extract only those correlations that are >0.6? w[w>0.6] #obviously doesn?t work, and I can?t find a way around it. I would very much appreciate any help! Best wishes Christoph (using R

Hi everyone, I'm having trouble applying the Cor() function to two matrices, both of which contain NAs. I am doing the following: a<-cor(m1, m2, use="complete.obs") ... and I get the following error message: Error in cor(m1, m2, use = "complete.obs") : no complete element pairs Does anyone know how I can apply a correlation, ignoring any NAs? Thanks, rcoder --