similar to: another aov question: unbalanced multiple responses

R provides a few ways of handling missing values, a.o. in the context of an anova (aov); 2 types of exclusion, and failure. In some situations, I personally like to have missing values replaced by the mean (or the median) for the given combination of factors. A routine that does that is something like the code included below. It works, but is (of course) rather slow. It would be much quicker

Concerns: R 1.5.0 gui version, Windows (downloaded binary) and Linux (installed from sources). # Load the data from the attached file: kk<-read.table("__filename__", header=1) # attach the data: attach(kk) Snr<-factor(Snr) # fool around with a call to anova.glm(): anova.glm( aov( nFD~Type+size+Modality+Error(Snr/(Type+size+Modality)) ) ) # Error: object nFD not found # Well, I

I commend you to (a) the recent article by Doug Bates on "Fitting nonlinear mixed models in R" pp. 27-30 in the latest issue of "R News" available from "www.r-project.org" -> Newsletter and (b) Doug's book with Pinheiro (2000) Mixed-Effects Models in S and S-PLUS (Springer). I suggest you try the same analysis using in "lmer", library(lme4), and

Dear colleagues, I've been searching for information on the Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy (MSA). This statistic is generated in SPSS and is often used to determine if a dataset is "appropriate" for factor analysis -- it's true utility seems quite low, but it seems to come up in stats classes a lot. It did in mine, and a glance through the R-help

I am trying to optimize a nested function using nlminb. This throws out an error that y is missing. Can someone help me with the correct syntax?? Thank you. test1 <- function(x,y) { sum <- x + y return(sum) } test2 <- function(x,y) { sum <- test1(x,y) sumSq <- sum*sum return(sumSq) } nlminb(start = c(1,1), test2,lower = c(0,0), upper = c(5,5)) -- View this message in

Hello Jean-Marc, **Resending.. not sure why subject got removed earlier** Below are the results that show test_unit_dft passes, but test_unit_mdct fails (only for nfft=480, 960, 1920) Note: Tested on BeagleboneBlack(Cortex-A8) fixed point on branch [1] ./test_unit_dft nfft=32 inverse=0,snr = 88.394372 nfft=32 inverse=1,snr = 93.896470 nfft=128 inverse=0,snr = 89.185895 nfft=128 inverse=1,snr =

Hi, Can you apply this change to the MDCT test and run it again. See if more (all) sizes pass. Given the results, I strongly suspect an overflow. Jean-Marc On 08/05/15 01:21 PM, Viswanath Puttagunta wrote: > Hello Jean-Marc, > > Below are the results that show test_unit_dft passes, but > test_unit_mdct fails (only for nfft=480, 960, 1920) > Note: Tested on

Hello Jean-Marc, Yep, that was it.. with your patch, test_unit_mdct passes for all nfft. So, what you do you suggest the next step here is? Regards, Vish On 8 May 2015 at 12:30, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi, > > Can you apply this change to the MDCT test and run it again. See if more > (all) sizes pass. Given the results, I strongly suspect an

Hello Jean-Marc, Below are the results that show test_unit_dft passes, but test_unit_mdct fails (only for nfft=480, 960, 1920) Note: Tested on BeagleboneBlack(Cortex-A8) fixed point on branch [1] ./test_unit_dft nfft=32 inverse=0,snr = 88.394372 nfft=32 inverse=1,snr = 93.896470 nfft=128 inverse=0,snr = 89.185895 nfft=128 inverse=1,snr = 93.537021 nfft=256 inverse=0,snr = 88.353151 nfft=256

On Wed, Feb 5, 2014 at 11:05 AM, Marcello Caramma (mcaramma) <mcaramma at cisco.com> wrote: > Hi, > > Apologies if this is a known issue, but running make on revision e3187444692195957eb66989622c7b1ad8448b06 fails one of the tests when using fixed point configuration (floating point is ok) on my linux x86. > Note that libopus1.1, as extracted from the tar ball, is OK. > >

Hi, this is my script > anova <- aov(data ~ Ts*Te*t + Error(R/Ts*Te*t)) > results <- summary(anova$Within) this is results Df Sum Sq Mean Sq F value Pr(>F) Ts 2 1232.2 616.11 53.606 3.965e-10 *** Ts:Te 4 4889.5 1222.37 106.356 4.075e-16 *** Ts:t 4 6472.1 1618.01 140.780 < 2.2e-16 *** Ts:Te:t 8 4181.0 522.63 45.473 1.088e-13 ***

Hi All, I am new to both Linux and Wine. I am running Mint 12. For work I use Stata, R, and PASS 11. I am able to install Stata and R as Linux apps. But PASS 11 is Windows only. I installed it using Wine and it appears to be installed. When I got to .wine/drive_c/Program Files/NCSS/PASS 11...I can see that all the files are there and when I either double click on PASS11.exe or use the

Hi, Apologies if this is a known issue, but running make on revision e3187444692195957eb66989622c7b1ad8448b06 fails one of the tests when using fixed point configuration (floating point is ok) on my linux x86. Note that libopus1.1, as extracted from the tar ball, is OK. Specifically, the tests that fail are in celt/tests/test_unit_mdct: nfft=32 inverse=0,snr = 85.341197 nfft=32 inverse=1,snr =

Hello, I'm building packages for Slackware and I've just tried to upgrade Slackware 13.37's CELT package to version 0.11.3, which apparently was released last year, but I've omitted it because it was not announced on the site. Anyway, now that I try build with the following configuration in my SlackBuild script: CFLAGS=$SLKCFLAGS -O2 \ CXXFLAGS=$SLKCFLAGS -O2 \

I have written some programs in Common Lisp and I have been using SAS to pipe those programs to my lisp compiler in batch mode by using the %xlog and %xlst SAS commands. I wonder if there is in R a similar way to pipe commands to LISP so that all my work would be concentrated in R even when I have to call a LISP program? I have looked at the foreign library but this seems to adjust data types not

Hi All, How do i calculate KMO for a dataset? *Dataset:---------------------* m1 m2 m3 m4 m5 m6 m7 m8 1 2 20 20 2 1 4 14 12 2 9 16 3 5 2 5 5 15 3 18 18 18 13 17 9 2 4 4 7 7 2 12 2 11 11 11 5 7 8 5 19 5 2 20 18 6 7 4 7 4 7 9 3 3 7 5 5 5 12 5 13 13 12 8 6 6 4 3 5 17 17 16 9 12 12 4 2 4 4 14 14 10 5 14

Actually, the SNR calculation in testenc has been broken for a while. The reason for taking the last frame was that the codec would introduce a one-frame latency. I changed that to half a frame (10 ms) a while ago and never updated testenc. Jean-Marc Le lun 01/09/2003 à 13:12, Mike Dunn a écrit : > Hi all, > > I'm new to the group. I'm looking at the speex code with an

Hi, I have an experimental design with 3 factors (Type, size and Modality), where the stimulus for Type==B, size==small was identical to that for Type==A, size==small. Since I am in the end only interested in Type==A, I "relabeled" all Type==B,size==small responses as Type==A,size==small. This gives me an unbalanced design, with a certain number of missing combinations, and others that

Ok. I did some quality tests. First off; never do quality tests with ints. I had serious problems interpreting my results until it dawned on me that the signal differences were just 0 or 1. So, after a lot of scratching my head, these are done comparing the result from the _float versions (which is how both resamplers work internally anyway). What I did was this: Load speex_wb.wav as one

Hi all, I'm new to the group. I'm looking at the speex code with an eye towards maybe helping out with either codec optimization or fixed-point implementation, The SNR calculation in testenc.c and testenc_uwb.c doesn't make sense to me. The code is { float enoise=0, esig=0, snr; for (i=0;i<FRAME_SIZE;i++) {