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Dear Berend, Thank you very much for proposing the limSolve-package! The lsei function of the package is exactly what I was looking for. Best regards Thomas -- View this message in context: http://r.789695.n4.nabble.com/Which-package...
Dear Mr. Barradas , Thank you very much! It works very well, especially defining a<-0 and using a<-a+1 as some kind of loop-count was exactly what i searched for! best regards Thomas -- View this message in context...
allvals <- rt(1000,df=11) ## 1000 samples is overkill: slightly more than ## 500*(1.05) should be large enough subvals <- (allvals[abs(allvals)<qt(0.975,df=11)]) vals <- m+subvals[1:500]*s/sqrt(n) I'm subsetting...
Dear All, Which package/function could i use to solve following linear least square problem? A over determined system of linear equations is given. The nnls-function may would be a possibility BUT: The solving is constrained with a inequality...
Dear R-users! I?m faced with following problem: Given is a sample where the sample size is 12, the sample mean is 30, and standard deviation is 4.1. Based on a Student-t distribution i?d like to...
Dear Richard, It is funny. I have to perform the approach of sediment fingerprinting for my master thesis. Mr. Hasselman gave me the advice to take a closer look into the limSolve package a few days ago. http://cran.r...
Dear All, I am using a specific approach for my master thesis. In essence, a supervised reclassification is used as an intermediate step to find chemical parameters which are able to reclassify defined groups. These variables will be used in...
Dear all, here is a example of my problem: /#data# g<-c(1,1,1,2,2,2) A<-runif(6,min=1,max=5) B<-runif(6,min=100,max=1000) C<-runif(6,min=30,max=31) D...
Dear R-experts, I would like to find the best variable combination which are maximises the accuracy of a cross validated reclassification. My data consists of 36 samples, equal distributed to 6 groups, and each sample are characterised by 20...
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