search for: ss1

Default arguments are evaluated in the function frame, not in the calling environment (nor in the same place as explicit arguments). > Which to me reads that a with statement as above is equivalent to > > > attach(data) ; aov.SS1(y=Obs) ; detach(data) > > Or is that just wishful thinking?? The latter. On Thu, 7 Oct 2004, RenE J.V. Bertin wrote: > Hello, > > I'm having a little argument with the 'with' function. I have > > > aov.SS1 <- function( y, indep=speed, fSnr=Subject, ......

dear all, I am stuck on the following problem. Give a string like ss1<- "z:f(5, a=3, b=4, c='1:4', d=2)" or ss2<- "f(5, a=3, b=4, c=\"1:4\", d=2)*z" I would like to remove all entries within parentheses.. Namely, I aim to obtain respectively "z:f()" or "f()*z" I played with sub() and gsub() but wit...

Hello, Try this. ss1 <- "z:f(5, a=3, b=4, c='1:4', d=2)" ss2 <- "f(5, a=3, b=4, c=\"1:4\", d=2)*z" fun <- function(s) sub("(\\().*(\\))", "\\1\\2", s) fun(ss1) #[1] "z:f()" fun(ss2) #[1] "f()*z" Hope this helps, Rui Barradas O...

...ot;, "()", s) It is essentially the same as Rui's suggestion, but I find the purpose to be more clear. It might also be a little more efficient. HTH Ulrik On Mon, 21 May 2018, 15:38 Rui Barradas, <ruipbarradas at sapo.pt> wrote: > Hello, > > Try this. > > > ss1 <- "z:f(5, a=3, b=4, c='1:4', d=2)" > ss2 <- "f(5, a=3, b=4, c=\"1:4\", d=2)*z" > > fun <- function(s) sub("(\\().*(\\))", "\\1\\2", s) > > fun(ss1) > #[1] "z:f()" > > fun(ss2) > #[1] "f()*z...

Hello, Is there a way to compare the relative relevance of fixed and random effects in mixed models? I have in mind measures of effect size in ANOVAs, and would like to obtain similar information with mixed models. Are there information criteria that allow to compare the relevance of each of the effects in a mixed model to the overall fit? Thank you, Bruno

...lso like to hear any suggestions on how I might further improve file system performance or my test methodology. The tests... # internal log mkfs.ext3 -v -O sparse_super -O dir_index -R stride=8 /dev/sda1 mount -t ext3 /dev/sda1 /mnt mkdir -m 777 /mnt/t bonnie++ -u nobody:nobody -d /mnt/t -s 4g -m ss1 -n128:20000:16:512 Version 1.03 ------Sequential Output------ --Sequential Input- --Random- -Per Chr- --Block-- -Rewrite- -Per Chr- --Block-- --Seeks-- Machine Size K/sec %CP K/sec %CP K/sec %CP K/sec %CP K/sec %CP /sec %CP ss1 4G 28235 94 38522 28...

...32 len) { + int32 i; + uint32 s1, s2; + schar *buf = (schar *)buf1; + + i = s1 = s2 = 0; + if (len > 32) { + const char mul_t1_buf[16] = {28, 0, 24, 0, 20, 0, 16, 0, 12, 0, 8, 0, 4, 0, 0, 0}; + __m128i mul_t1 = sse_load_si128((__m128i_u*)mul_t1_buf); + __m128i ss1 = _mm_setzero_si128(); + __m128i ss2 = _mm_setzero_si128(); + + for (i = 0; i < (len-32); i+=32) { + // Load ... 2*[int8*16] + __m128i in8_1 = sse_load_si128((__m128i_u*)&buf[i]); + __m128i in8_2 = sse_load_si128((__m128i_u*)&buf[i + 16]); +...

Een ingesloten tekst met niet-gespecificeerde tekenset is van het bericht gescrubt ... Naam: niet beschikbaar Url: https://stat.ethz.ch/pipermail/r-help/attachments/20071029/b29e9bd5/attachment.pl

...len) +{ + int32 i; + uint32 s1, s2; + schar *buf = (schar *)buf1; + + i = s1 = s2 = 0; + if (len > 32) { + const char mul_t1_buf[16] = {28, 0, 24, 0, 20, 0, 16, 0, 12, 0, 8, 0, 4, 0, 0, 0}; + __m128i mul_t1 = sse_load_si128((void const*)mul_t1_buf); + __m128i ss1 = _mm_setzero_si128(); + __m128i ss2 = _mm_setzero_si128(); + + for (i = 0; i < (len-32); i+=32) { + // Load ... 2*[int8*16] + __m128i in8_1 = sse_load_si128((void const*)&buf[i]); + __m128i in8_2 = sse_load_si128((void const*)&buf[i + 16]);...

...- I was wrong. I think I am too stupid to create the correct subset for phase 2. Phase1: Sample 1000 parts with 80 defective. Phase2: Sample 100 parts out of these 1000 with 15 defective. 0:ok, 1:defunct. The table below gives the conditional sampling values. Please help me: library(survey) ss1 <- data.frame(id=1:1000, ph1.x=rep(c(1,0),c(10,990)), subset=rep(c(1,0),c(100,900)), ph2.y=rep(c(1,0,NA),c(15,85,900)), n1=rep(1000,1000), n2=rep(100,1000) ) table(ss1$ph1.y, ss1$ph2.x) > Phase1.x >Phase2.y 0 1 > 0 85 0 > 1 5 10 p2 <- twophase(id=list(...

...2; > + schar *buf = (schar *)buf1; > + > + i = s1 = s2 = 0; > + if (len > 32) { > + const char mul_t1_buf[16] = {28, 0, 24, 0, 20, 0, 16, 0, 12, > 0, 8, 0, 4, 0, 0, 0}; > + __m128i mul_t1 = sse_load_si128((void const*)mul_t1_buf); > + __m128i ss1 = _mm_setzero_si128(); > + __m128i ss2 = _mm_setzero_si128(); > + > + for (i = 0; i < (len-32); i+=32) { > + // Load ... 2*[int8*16] > + __m128i in8_1 = sse_load_si128((void const*)&buf[i]); > + __m128i in8_2 = sse_load_si128((...

...char *)buf1; >> + >> + i = s1 = s2 = 0; >> + if (len > 32) { >> + const char mul_t1_buf[16] = {28, 0, 24, 0, 20, 0, 16, 0, 12, >> 0, 8, 0, 4, 0, 0, 0}; >> + __m128i mul_t1 = sse_load_si128((void const*)mul_t1_buf); >> + __m128i ss1 = _mm_setzero_si128(); >> + __m128i ss2 = _mm_setzero_si128(); >> + >> + for (i = 0; i < (len-32); i+=32) { >> + // Load ... 2*[int8*16] >> + __m128i in8_1 = sse_load_si128((void const*)&buf[i]); >> + __m128i...

Hello all, We've been using samba version 3.0.4 on RH9 with success for quite a while now for shares on our domain (DOM1). Since this machine will have to be available in the near future in another domain (DOM2) as a webserver, and limited fileserver, another network interface has been added for the NIC. When browsing the shares from a WIN98SE computer in DOM2, we are able to see the

Hello, I was doing a linear regression with the following formula: lm(y~x+0), so it passes through the origin. But when I called the summary of the regression i saw that R squared is abnormally high (it's a lot lower in other programs such as SigmaPlot and MS Excel).The manual explained the cause of the difference (because of the different computing method), but what should I do to get the

...s2; > + schar *buf = (schar *)buf1; > + > + i = s1 = s2 = 0; > + if (len > 32) { > + const char mul_t1_buf[16] = {28, 0, 24, 0, 20, 0, 16, 0, 12, > 0, 8, 0, 4, 0, 0, 0}; > + __m128i mul_t1 = sse_load_si128((__m128i_u*)mul_t1_buf); > + __m128i ss1 = _mm_setzero_si128(); > + __m128i ss2 = _mm_setzero_si128(); > + > + for (i = 0; i < (len-32); i+=32) { > + // Load ... 2*[int8*16] > + __m128i in8_1 = sse_load_si128((__m128i_u*)&buf[i]); > + __m128i in8_2 = sse_load_si128((_...

...files(ss))) [1] FALSE Warning messages: 1: In file.remove(file.path(ss, list.files(ss))) : cannot remove file '..... my folder path...', reason 'Read-only file system' Also when I tried to delete a single Locked file, I am getting following error: Warning message: In file.remove(ss1) : cannot remove file '/..... my folder path...', reason 'Operation not permitted' I am using Mac with OS : 10.7.5 Could you please help me with correct R code?

What do you base this on? Per https://gcc.gnu.org/onlinedocs/gcc/x86-Options.html : "For the x86-32 compiler, you must use -march=cpu-type, -msse or -msse2 switches to enable SSE extensions and make this option effective. For the x86-64 compiler, these extensions are enabled by default." That reads to me like we're fine for SSE2. As stated in my comments, SSSE3 support must be

...haracter. Quiero convertirlas justamente a un vector numeric (o mejor aun dentro del mismo data.frame que sean numeric) para poder operar con ellas (los valores que no sean números deberían quedar como NA). Probé con <-as.numeric(as.character(SS)) pero me devuelve valores NA. También probé con SS1<- type.convert(SS, na.strings = "NA", as.is = FALSE, dec = ",", numerals = c("allow.loss", "warn.loss", "no.loss")) y luego con as.numeric pero me devuelve los números de ordenación de niveles del factor (creo) Muy agradecido de antemano por cua...

...e_sizes<- matrix(c(10,10,10,25,25,25,25,50,25,100,50,25,50,100,100,25,100,100), nrow=2) # see what it looks like sample_sizes ssds<-c(4,4.4,5,6,8) nssds<-length(ssds) results<-list() # first loop steps through the sample for(ss in 1:dim(sample_sizes)[2]) { # get the two sample sizes ss1<-sample_sizes[1,ss] ss2<-sample_sizes[2,ss] then step through your SDs: ssd_index<-1 for(ssd in ssds) { # generate the two samples with the SDs sample1<-rnorm(ss1,ssd) sample2<-rnorm(ss2,ssd) # here run your tests, recording the results that you want results[[(ss-1)*ns...

..., sum, na.rm=T) > ire1 <- data.frame(md1[, 1:11], other) Error in data.frame(md1[, 1:11], other) : arguments imply differing number of rows: 11, 75 --------------------------------------------- I have simply worked around the problem by using ire1 <- data.frame(md1$site, md1$colour, md1$ss1 ... , other) but I would like to know what stupid thing I am doing. Thanks