similar to: working with sparse matrix

Dear all, I would like to ask your help concerning an error message I get. I have the following struct str(CRagentInTime[[1]]) List of 2 $ timelag: int 0 $ CRagent:List of 50 ..$ :List of 3 .. ..$ CRmap: num [1:256, 1:256] NA NA NA NA NA NA NA NA NA NA ... .. ..$ xy : num [1:2] 10 177 .. ..$ sr : num [1:49] -94.9 -92.8 -79.5 -97.6 -78.4 ... and I wanted to select all the sr fields

Hi All,  In order to compare two different logistic regressions, I think I need to compare them based on their BIC values, but I am not sure if the smaller BIC would mean a better model or the reverse is true? Thanks a lot,Andra [[alternative HTML version deleted]]

Hi, all: Does anybody know how to avoid the intercept term in cv.glmnet coefficient? When I say "avoid", it does not mean using coef()[-1] to omit the printout of intercept, it means no intercept at all when doing the analysis. Thanks. [[alternative HTML version deleted]]

Hi My data looks like this startDate="2008-06-01" dateRange =c( "2008-10-01","2008-12-01") Is there any method to find the week number from the startDate range ----- Thanks in Advance Arun -- View this message in context: http://r.789695.n4.nabble.com/Week-number-from-a-date-tp4410223p4410223.html Sent from the R help mailing list archive at Nabble.com.

Hi all, I am using the glmnet R package to run LASSO with binary logistic regression. I have over 290 samples with outcome data (0 for alive, 1 for dead) and over 230 predictor variables. I currently using LASSO to reduce the number of predictor variables. I am using the cv.glmnet function to do 10-fold cross validation on a sequence of lambda values which I let glmnet determine. I then take

Yes, that will halve the number of multiplications. If you?re looking for such optimisations then you can also consider ifelse(G=='male', 65L, 58L). That will definitely use less time & memory if WC is integer, but the trade-offs are more complicated if WC is floating point. Regards, Jorgen Harmse. From: avi.e.gross at gmail.com <avi.e.gross at gmail.com> Date: Friday,

Just a minor point in the suggested solution: df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) since WC and TG are not conditional, would this be a slight improvement? df$LAP <- with(df, TG*(WC - ifelse(G=='male', 65, 58))) -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of Jorgen Harmse via R-help Sent: Friday,

Hi R users I apologise in advance for this question as I suspect it is simple and perhaps others have had this problem. I am struggling to sort out how to fix the x axes so that the labels don't overlap. I have put the following example together to show my problem. library(lattice) titre <- as.factor(rep(c(10999,20999,30999,40999,50999,60999,

Hello, I appreciate this is likely to be an easy question. I am trying to obtain the residuals from a linear regression where the line is forced to have a 1:1 relationship. An example of the data: A<-c(0.9803922, 1.3850416, 0.8241758, 0.0000000, 0.4672897, 1.1904762, 0.0000000, 0.9456265, 1.5151515) B<-c(1.3229572, 1.9471488, 1.3182674, 0.7007708, 1.0185740, 1.0268562, 0.8695652,

Hello all, I've been working on a package to do various things related to the Conway-Maxwell-Poisson distribution and wanted to be able to make fast random draws from the distribution. My R code was running quite slow so I decided to give Rcpp a bash. I had used it before but only for extremely basic stuff and always using inline. This time I decided to give making a proper package a go.

df$LAP <- with(df, ifelse(G=='male', (WC-65)*TG, (WC-58)*TG)) That will do both calculations and merge the two vectors appropriately. It will use extra memory, but it should be much faster than a 'for' loop. Regards, Jorgen Harmse. ------------------------------ Message: 8 Date: Fri, 3 Nov 2023 11:10:49 +1030 From: "Md. Kamruzzaman" <mkzaman.m at gmail.com>

Dear, I would like know the way to calculate the variance explained of a regression tree. I use the function "ctree" from library "party" many thanks [[alternative HTML version deleted]]

Dear subscribers, I am looking for a function which would allow me to model the dependent variable as the number of successes in a series of Bernoulli trials. My data looks like this ID TRIALS SUCCESSESS INDEP1 INDEP2 INDEP3 1 4444 0 0.273 0.055 0.156 2 98170 74 0.123 0.456 0.789 3 145486 30 0.124

Hi, I must be doing something silly here, because I can't get the studentised and standardised residuals from r output of a linear model to agree with what I think they should be from equation form. Thanks in advance, Jennifer x = seq(1,10) y = x + rnorm(10) mod = lm(y~x) rstandard(mod) residuals(mod)/(summary(mod)$sigma) rstudent(mod)

Hi All,  I am trying to run cv.glmnet(x,y,family="multinomial", nfolds =4) and I only have 8 observations and the number of features I have is 1000, so my x matrix is 8 by 1000 and when I run the following, I get this error, I am not sure what is causing this problem.  Error in predmat[which, , seq(nlami)] = preds :   number of items to replace is not a multiple of replacement length Can

Hi,   Could any one please help how I can transform data based on Box-Cox Transformations in R.   Any helps will be much appreciated.   thanks, Kagba [[alternative HTML version deleted]]

Dear members of R forum, I'm trying to perform a simply dynamic programming model in R, following the reccomendations of Soetart & Herman (A practical guide to ecological modeling). However, I've obtained a number of problems, that I'm unable to solve (even thoughI've tried during at least 2 hours). Can anyone help me? Many thanks > ccrit <- 0 > cmax <- 5 >

Hi users I'm student who is struggling with basic R programming. Would you please help me with this problem. "My english is bad" I hope that my question is clear: I have a matrix in wich there are two colmns( yp, yt) Yp: predicted values from my model. yt: true values ( my dependante variable y is a categorical;3 modalities (0,1,2) I don't know how to procede to calculate the

Hi everyone, I have a zero vector of length N and I would like to randomly allocate the value 1 to one of the values of this vector. I presume I have to use the uniform distribution but could someone tell me how I should process? Thanks in advance, Boris -- View this message in context: http://r.789695.n4.nabble.com/generate-randomly-a-value-of-a-vector-tp3798190p3798190.html Sent from the R

This mean First, I am no expert but I am analyzing some marketing data. I have information on two versions of the same site, and I have data on the number of times people filled out a form on each version of the site. Sample data: Site 1 Site 2 Filled out form 10 35 Did not fill out form 50