search for: 1.00

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

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 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

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

Hi, I have a problem using the function 'reshape' for the following dataset: input: X Y Z T.U.1 T.U.2 T.V.1 T.V.2 1.00 1.00 A 24.94 24.74 34.65 35.33 1.00 3.00 A 26.03 25.87 25.76 26.12 1.00 1.00 B 24.76 24.63 34.34 34.48 1.00 3.00 B 26.15 25.98 25.96 25.66 2.00 1.00 A 24.40 24.26 34.55

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 -

Hi all, I have the folowing frame(there are more columns than shown), 1 2 3 4 5 Year Total Tus Whi Norw 1994 1.00 1830 0 355 1995 1.00 0 0 0 1995 1.00 0 0 0 1995 1.00 4910 4280 695 1997 1.00 0 0

Hi all, I have the folowing frame(there are more columns than shown), 1 2 3 4 5 Year Total Tus Whi Norw 1994 1.00 1830 0 355 1995 1.00 0 0 0 1995 1.00 0 0 0 1995 1.00 4910 4280 695 1997 1.00 0 0

I start a clean session of R 1.9.1 on Windows and I run the following code: > library(MASS) > data(painters) > pca.painters <- princomp(painters[ ,1:4]) > loadings(pca.painters) Loadings: Comp.1 Comp.2 Comp.3 Comp.4 Composition 0.484 -0.376 0.784 -0.101 Drawing 0.424 0.187 -0.280 -0.841 Colour -0.381 -0.845 -0.211 -0.310 Expression 0.664 -0.330 -0.513

Dear All, I have a data frame like this: name ip Bsent Breceived a 1 0.00 0.00 a 2 1.43 19.83 a 1 0.00 0.00 a 2 1.00 1.00 b 1 0.00 2.00 b 3 0.00 2.00 b 2 2.00 0.00 b 2 2.00 0.00 b 1 24.40 22.72 c

I try to utilize some operations on rows in a matrix using command 'apply' but find a problem. First I write a simple function to normalize a vector (ignore error handling) as follows: normalize = function( v ) { return( ( v-min(v) ) / ( max(v) - min(v) ) ) } The function works fine for a vector: > normalize( 1:5 ) [1] 0.00 0.25 0.50 0.75 1.00 Then I generate a matrix: > a =

Hi all, I've got a matrix of fractional data that is all positive and greater than zero that I would like to "loosely" classify, for lack of a better word. It looks something like this : 1.07 1.11 1.27 1.59 0.97 0.76 2.23 0.98 0.71 0.88 1.19 1.02 What I'm looking for is a way to round these numbers to the nearest 0.25, i.e. the above matrix would be

Hi, I'm trying to create a distance matrix. And it works out somewhat ok. However, I suspect that there are some efficiency issues with my efforts. Plz have a look at this: donor <- matrix(c(3,1,2,3,3,1,4,3,5,1,3,2), ncol=4) receiver <- matrix(c(1,4,3,2,4,3,1,5,1,3,2,1,4,5,3,5,1,3,2,4,5,1,2,3,1,4,5,5,1,2,1,3,4,3,2,5,5,1,4,2,5,4,3,2), ncol=4) The above creates my two matrices. I have

Hi all, Here is my problem: I performed bioassays using a unique insecticide on 9 different genotypes and got their mortality depending on the dose of insecticide used. Now, I want to see wether some genotypes are different or not in their responses to insecticide. My problem is that I have up to four replicates for some genotypes, but only one for other... Due to this unbalanced design, I

When printing a table it is broken at some point (depending how long are the associated names) >>> see example below. Is there a way to control number of columns being printed for a given chunk of the table? Best regards, Ryszard > z5 AAAAAAA BBBBBBB CCCCCCC DDDDDDD EEEEEEE FFFFFFF GGGGGGG HHHHHHH IIIIIII AAAAAAA 1.00 -0.69 -0.54 -0.88 NA NA NA

Hi R users, Is there an easy way in R to generate the results table below using table 1 and the formula (simplified version of the real problem)? It would be easy if I knew the R equivalent of SAS's retain function, but could not find one. Thanks in Advance for any help! table1: ID X2 X3 1.00 1.00 0 2.00 0.00 3.00 1.00 4.00 3058 5.00 0.00 6.00 6.00 Formula: X3 = x2 + (.24 *

Hi all, I have to produce arrangements of 25 simple plots of the type plot(x,y,pch=".") where there are typically on the order of 20000 points. So, overall, I have about 500000 points. When I use the pdf device, I get file sizes (on a Windows machine) of about 10 MB. When I then zip the files, I'm down to about 0.5MB, so the original pdf files were created with a lot of

All of our Kafka clusters are fairly write-heavy. The cluster in question is our second-heaviest ? we haven?t yet upgraded the heaviest, due to the issues we?ve been experiencing in this one. Here is an iostat example from a host within the same cluster, but without the RAID check running: [root at r2k1 ~] # iostat -xdmc 1 10 Linux 3.10.0-327.13.1.el7.x86_64 (r2k1) 05/27/16 _x86_64_ (32 CPU)

On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very

I am an R newbie, and I am facing what is for me a challenging problem. I am trying to write functions to solve the following problems. It seems as though R offers so many options I am not sure how to approach the problem. I have a data frame with dates in the first column and returns in the remaining columns. I would like to give a user a variety of options. I designate Series1 as the