similar to: R [loop statement ]

Always keep the mailing list in cc. The code runs for each row in the data. However I get the feeling that there is a mismatch between what you think that is in the data and the actual data. ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070

Dear anonymous, The big mistake in the output might be obvious to you but not to others. Please make clear what the correct output should be or at least what is wrong with the current output. And please DO read the posting guide which asks you not to post in HTML. ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie &

hi, i am new in this field. do favorite<http://stackoverflow.com/questions/36404707/simulation-study-of-2-sample-test-on-different-combination-of-factors#> If I wish to conduct a simulation on the robustness of two sample test by using R language, is that any ways in writing the code? There are several factors (sample sizes-(10,10),(10,25),(25,25),(25,50),(25,100),50,25),(50,100),

Hi, i am sorry, the output should be values between 0 and 0.1 and not supposed to be 1.00, it is because they are type 1 error rate. And now i get output 1.00 for several samples,rhis is no correct. The loop do not run for every row. i do not know where is my mistake. As i use the same concept on normal distribution setup, i get the result. Sent from my phone On Thierry Onkelinx

HI, I am trying to use switch () function to connect the three distribution (normal ,gamma with equal skewness and gamma with unequal skewness. But i am losing my ideas since i have sample sizes-(10,10),(10,25),(25,25),(25,50),(25,100),50,25),(50,100), (100,25),(100,100) standard deviation ratio- (1.00, 1.50, 2.00, 2.50, 3.00 and 3.50) distribution of gamma distribution with unequal skewness

i have combined all the variables in a matrix, and i wish to conduct a simulation row by row. But i found out the code only works for the every first row after a cycle of nine samples. But after check out the code, i don know where is my mistake... can anyone pls help .... #For gamma disribution with equal skewness 1.5 #to evaluate the same R function on many different sets of data

This is my current work.Now i am trying to use a function to do the normal distribution simulation. rm(list=ls()) t <- u<- mann<- rep(0, 45) Nsimulation<-function(S1,S2,Sds,nSims) { set.seed(1) for (sim in 1:nSims) { matrix_t <-matrix(0,nrow=nSims,ncol=3) matrix_u<-matrix(0,nrow=nSims,ncol=3)

You can make this much more readable with apply functions. result <- apply( all_combine1, 1, function(x){ p.value <- sapply( seq_len(nSims), function(sim){ gamma1 <- rgamma(x["m"], x["sp(skewness1.5)"], x["scp1"]) gamma2 <- rgamma(x["n"], x["scp1"], 1) gamma1 <- gamma1 -

You have quite a few mistakes in your example. The code below works for me - you can wrap it in a function if you like. I think you will need a lot more practice before you can write something like this in R as you are missing close braces and haven't really worked out the difference between the number of calculations you are doing for each replication and the number of replications. It takes

Hi, i think i have figured the purpose of using this index (i-1)*5+j in the previous example that you gave. It is because that i have to consider the outer loop and inner loop also... so the iterative for i need to minus one because it have ran one times simulation already ,then times the number of sizes of inner loop, then plus the iterative of j.... then for the simulation, i think there will

Hi, I am new-comer to statistics and R-Project. I would like to know if these features can be attained in R-Project.Please help. 1) beta 1 and Beta 2, or gamma one and gamma two for skewness and kurtosis, respectively, including standard errors and tests for significance (relative to values for a Gaussian distribution). 2) linear correlation 3) quadratic regression 4) polynomial regression

Hi Si Jie, Again, please send questions to the list, not me. Okay, I may have worked out what you are doing. The program runs and produces what I would expect in the rightmost columns of the result "g". You are storing the number of each test for which the p value is less than 0.05. It looks to me as though the objects storing the results should be vectors as you are only storing 100 p

Is there some reasonable way to generate random data from a distribution that has some degree of skewness and/or kurtosis, but would otherwise be normal? thanks, -------------- next part -------------- A non-text attachment was scrubbed... Name: greiff.vcf Type: text/x-vcard Size: 398 bytes Desc: Card for Warren R. Greiff Url :

Well fellow R users, I throw myself on your mercy. Help me, the unworthy, satisfy my employer, the ungrateful. My feeble ramblings follow... I've searched R-Help, the R Website and done a GOOGLE without success for a one way ANOVA procedure to analyse data that are both non-normal in nature and which exhibit unequal variances and unequal sample sizes across the 4 treatment levels. My

Hello, In the past I have used "expression" to include greek letters in axis labels, but this time I need to include the greek letter as part of a legend. Basically, I need to create the following vector to rename the levels of a factor: c("Interferon-gamma", "IL-10", "IL-5"), where "gamma" obviously needs to be printed as the greek letter

Hi Jeem, First, please send questions like this to the help list, not me. I assume that you are in a similar position to sjtan who has been sending almost exactly the same questions. The problem is not in the loops (which look rather familiar to me) but in your initial assignments at the top. For instance: scale parameter=(1,1.5,2,2.5,3) produces an error which has nothing to do with the

Full_Name: Ximing Zhao Version: R 1.7.1 OS: MacOs X Submission from: (NULL) (64.136.27.51) When I used function plot in R 1.7.1, I found two bugs. My whole function is this: ***************** drawexp<-function(X,x,c,b){ exp<-function28(X,x,c,b) if(max(exp)>=max(dexp(x,rate=1))){ plot(x,exp, type="l",main= paste("Exponential ,n=",length(X),"

Hi, Dear R-help I know there are some R package to deal with zero-inflated count data. But I am now looking for R package to deal with zero-inflated continuous data. The response variable (Y) in my dataset contains a larger mount of zero and the Non-zero response are quite right skewed. Now what i am doing is first to use a logistic regression on covariates (X) to estimate the probability of Y

hello all happy new year and hope you r having a good holiday. i would like to calculate the expectation of a particular random variable and would like to approximate it using a number of the functions contained in R. decided to do some experimentation on a trivial example. example ======== suppose x(i)~N(0,s2) where s2 = the variance the prior for s2 = p(s2)~IG(a,b) so the posterior is

lrm does some binning to make the calculations faster. The exact calculation is obtained by running f <- lrm(...) rcorr.cens(predict(f), DA), which results in: C Index Dxy S.D. n missing 0.96814404 0.93628809 0.03808336 32.00000000 0.00000000 uncensored Relevant Pairs Concordant Uncertain 32.00000000