Re: [R] Student-t distributed random value generation within a confidence interval?

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 lt;- m+subvals[1:500]*s/sqrt(n) I'm subsetting before transforming, it seems slightly easier. lt;/quote Thank you very much

[R] Student-t distributed random value generation within a confidence interval?

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 simulate randomly 500 possible mean values within a two-tailed 95% confidence interval. Calculation of

Re: [R] Which package/function for solving weighted linear least squares with inequality and equality constraints?

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:

Re: [R] Optimization in R similar to MS Excel Solver

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-project.org/web/packages/limSolve/index.html I guess, the lsei-function of

[R] Linear discriminant function analysis based median as group centroid and nonparametric scale estimators???

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 a next step where location and scale estimators of the

[R] store the results of two connected and disturbed for-loops to data.frame

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-runif(6,min=67,max=98765) var-cbind(A,B,C,D) label-colnames(var) store-data.frame(matrix(ncol=2)) colnames(store)=c(usedVar,prediction)

Re: [R] store the results of two connected and disturbed for-loops to data.frame

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:

[R] random variable selection algorithms for lda?

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 variables. /data-data.frame(1:36,1:20)