similar to: Repeated Measure different results to spss

Hi, I have a 3d array as below, I want to make this array to a matrix of p=50(rows) and n=20(columns) with the coverage values . The code before the array is: library(binom) Loading required package: lattice pi.seq<-seq(from = 0.01, to = 0.5, by = 0.01) no.seq<-seq(from = 5, to = 100, by = 5) cp.all = binom.coverage( p = pi.seq, n = no.seq , conf.level = 0.95, method = "exact")

Dear R Users,i am very new to R. I want your help on an issue regarding distance matrix and cluster analysis i had discharge data of 4 rivers(a,b,c,d) in 4 vectors each having 364 values > dput(qmu)structure(list(a = c(0.26, 0.25, 0.25, 0.25, 0.24, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,

Hello~   Did any one have used the package 'orcutt' ?   I find that it can not work smoothly in a single variable regression. I use the example following, it function very well.   But when I regress "cons" on "price" (use the "reg1<-lm(cons~price+income+temp)") , then  use "reg11<-cochrane.orcutt(reg1) ". There is an error message “Error in

Folks, I'm trying to get stats from a matrix for each transition from one state to another. I have a matrix x as below. structure(c(0, 2, 2, 2, 0, 0, 0, 1, 1, 1, 1, 2, 2, 1, 1, 1, 0, 0, 2, 2, 0.21, -0.57, -0.59, 0.16, -1.62, 0.18, -0.81, -0.19, -0.76, 0.74, -1.51, 2.79, 0.41, 1.63, -0.86, -0.81, 0.39, -1.38, 0.06, 0.84, 0.51, -1, -1.29, 2.15, 0.39, 0.78, 0.85, 1.18, 1.66, 0.9, -0.94,

Dear All, I am analysing some data for a colleague (not my data, gotta be published so I cannot divulge). My response variable is the number of matings observed per day for some fruitlies. My factors are: Day: the observations were taken on 9 days Regime: 3 selection regimes Line: 3 replicates per selection regime. I have 81 observations in total The lines are coded A to I, so I do not need

I have ran across a case where the function isIdenticalTo is return true for instructions that are not equivalent. The instructions in question are load/store instructions, and is causing a problem with MachineBranchFolding. The problem is this, I have two branches of a switch statement that are identical, except for the size of the store. Here is some cut-down LLVM-IR to showcase the issue:

I have a problem with R. I try to compute the confidence interval for my df. When I want to create the plot I have this problem: Error in xy.coords(x, y, xlabel, ylabel, log) : 'x' and 'y' lengths differ. I try this code: library(dplR) df.rwi <- detrend(rwl = df, method = "Spline",nyrs=NULL) write.table(df.rwi,file="rwi.txt",quote=FALSE,row.names=TRUE)

Is there any way to get printf type functionality inside the kernel from dtrace probes. Basically I want to dump progress through flow in my device driver. Something like: DTRACE_PRINTF("Inside chip reset, mailboxes %x %x %x %x %x %x %x %x", mb1, mb2, .....); ... ... DTRACE_PRINTF("reset failed: reason %s", failure_reasons[err]); I may have several such probes and they may

Hi, My MUA (claws-mail) is having a hard time listing directories for a mail account with two namespaces, one of which using mbox and the other one using maildir to store mails. Let's call the namespaces "#mbox." and "#maildir." and have "." as separator. Assume I have the following folder hierarchy: $namespace $namespace folder $namespace folder folder1a

On Jan 4, 2011, at 11:08 AM, Villmow, Micah wrote: > I have ran across a case where the function isIdenticalTo is return true for instructions that are not equivalent. The instructions in question are load/store instructions, and is causing a problem with MachineBranchFolding. The problem is this, I have two branches of a switch statement that are identical, except for the size of the store.

Hello All, I have a simple question based on how things are labeled on my heat map; particularly, there is this annoying "X" that appears before the numeric value of all the labels of my columns. Let's say I have the following silly data, stored in "temp.txt" 1905 1910 1950 1992 2011 2020 Gnat 0.08 0.29 0.29 0.37 0.39 0.43 Snake

Greetings.? My wife is teaching an introductory stat class at UC Davis.? The class emphasizes the use of simulations, rather than mathematics, to get insight into statistics, and R is the mandated tool.?? A student in the class recently inquired about different approaches to sampling from a binomial distribution.? I've appended some code that exhibits the idea, the gist of which is that using

Duncan, Below are the tabulated compile times and executable sizes. A) gcc 4.5.4svn using -msse3 -ffast-math -O3 -fno-tree-vectorize B) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize -fplugin-arg-dragonegg-enable-gcc-optzns C) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize Compile time (seconds) Benchmark A) stock B) gcc 4.5.4/ C)

Dear list, I have observed a weird behaviour from R --- apologies if I am missing something obvious! df3f826f28 df3f826f28 Say you type in R: >c.preec <- 10074 >c.gd <- 2200 >p1 <- .2 >c.neo <- p1*9451 + (1-p1)*3883 >n.preec <- 3710 >n.gd <- 2650 >n.neo <- 2120 >n.pcos <- 53000 >unit.met <- 94 >cost.met <- 94*n.pcos >effect <-

Hi All, In the script below, the importance measure for column 4 (ie MeanDecreaseGini) indicated "Inf" for V7. Running the getTree command showed that "V7" had been selected at least twice in one of the trees for Random Forest. So the "Inf" command was not generated as a result of dividing the sum of the decreases by 0. Any suggestions on what may be causing the

Hi Jack, thanks for doing this. > Below are the tabulated compile times and executable sizes. > > A) gcc 4.5.4svn using -msse3 -ffast-math -O3 -fno-tree-vectorize > B) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize -fplugin-arg-dragonegg-enable-gcc-optzns > C) gcc 4.5.4svn/dragonegg using -msse3 -ffast-math -O3 -fno-tree-vectorize These numbers really

aa <- (structure(list(X.0.85 = c(-1.02, -1.17, -1.29, -1.39, -1.46, -1.5, -1.52, -1.5, -1.46, -1.39, -1.3, -1.19, -1.07, -0.93, -0.79, -0.65, -0.5, -0.36, -0.22, -0.08, 0.05, 0.18, 0.3, 0.41, 0.52, 0.62, 0.72, 0.81, 0.89, 0.98, 1.05, 1.13, 1.19, 1.25, 1.29, 1.31, 1.31, 1.29, 1.24, 1.16, 1.06, 0.93, 0.77, 0.58, 0.38, 0.16, -0.07, -0.31, -0.89, -1.05, -1.19, -1.31, -1.41, -1.47, -1.51, -1.51,

Dear all,   I did ANOVA for many response variables (Var1, Var2, ....Var75000), and i got the result of p-value like below. Now, I want to select those predictors, which have pvalue less than or equal to 0.05 for each response variable. For example, X1, X2, X3, X4, X5 and X6 in case of Var1, and similarly, X1, X2.......X5 in case of Var2, only X1 in case of Var3 and none of the predictors in case

I'm trying to write a function to find the means over factors of the responses in a mlm (something I would do easily in SAS with PROC SUMMARY). The not-working stub of a function to do what I want is below, and my problem is that I don't know how to call aggregate (or some other function) in the context of terms in a linear model extracted from a lm/mlm object. means.mlm <-

On Mon, Dec 16, 2013 at 04:16:29PM -0800, Michael Dalton wrote: > Commit 2613af0ed18a ("virtio_net: migrate mergeable rx buffers to page frag > allocators") changed the mergeable receive buffer size from PAGE_SIZE to > MTU-size, introducing a single-stream regression for benchmarks with large > average packet size. There is no single optimal buffer size for all >