similar to: sample size for t-tests

Hello, I'm very new to using R, but I was told it could do what I want. I'm not sure how best to enter the information but here goes... I'm trying to transfer the following integral into R to solve for ln(gamma_1), on the left, for multiple instances of gamma_i and variable N_i. gamma_i is, for example, (0, 0.03012048, 0.05000000, 0.19200000, 0.44000000, 0.62566845) N_i (N_1 or

Hello! I have a csv file of intra-day financial data (5-min closing prices) that looks like this: (obs - the dates are formated as day/month/year, as is usual here in Brazil) Date;Time;Close 01/09/2009;10:00;56567 01/09/2009;10:05;56463 01/09/2009;10:10;56370 ##(goes on all day) 01/09/2009;16:45;55771 01/09/2009;16:50;55823 01/09/2009;16:55;55814 ##(jumps to the subsequent day)

I'm wondering how odds ratio is computed. I thought that it is (n11/n12)/(n21/n22), but it is not what fisher.test() computes. Could somebody let me know? > n11=3 > n12=1 > n21=1 > n22=3 > > n1_=n11+n12 > n2_=n21+n22 > > n_1=n11+n21 > n_2=n12+n22 > > x=rbind(c(n11,n12),c(n21,n22)) > > threshold=dhyper(n11,n1_,n2_,n_1) >

Dear R users, how can I test, whether two correlations differ significantly. (I want to prove, that variables are correlated differently, depending on the group a person is in.) Greetings from Freiburg im Breisgau (Germany), Timo Stolz

Hola eRReros. Os lo explico con un ejemplo: # Cargamos los paquetes y el ejemplo install.packages("SPEI") library("SPEI") data(wichita) # los primeros 12 datos head(wichita,12) # mi subset de los primeros 12 datos meu<-wichita[c(1:12),] meu # como veis los valores de TMED son iguales en ambos dataframes. # ahora viene el problema # calculamos

Dear all Just for fun, I have just downloaded the paper mentioned below and checked it with R-1.6.1. Everything is ok with exception of Table 2b, where I get always 1 instead of 0.5: > pbinom(1e15,2e15,0.5) [1] 1 Which value should be correct? Best regards Christian Stratowa ============================================== Christian Stratowa, PhD Boehringer Ingelheim Austria Dept NCE Lead

Dear R developers and users: I have the following data, x is the response vaiable, nsample(individual) nested within trt, and subsample nested within nsample, I want to fit trt as fixed effect, and block, nsample(trt) as random effects using lme, is the following coding correct? dat$vgrp <- getGroups(dat, form = ~ 1|trt/nsample, level = 2) ge.lme1 <- lme(fixed=x~trt, data=dat,

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

Hello, i wrote this function guete and now i want to plot it: but i get this error message. i hope someone can help me. Error in dim(robj) <- c(dX, dY) : dims [product 16] do not match the length of object [1] p_11=seq(0,0.3,0.1) p_12=seq(0.1,0.4,0.1) guete = function(p_11,p_12) { set.seed(1000) S_vek=matrix(0,nrow=N,ncol=1) for(i in 1:N) { X_0=rmultinom(q-1,size=1,prob=p_0)

Btw, here is another interesting paper about post-dominators and control dependence: https://pdfs.semanticscholar.org/cbb2/9a0e4895025bd9df24f9263217df12f1ed1e.pdf I think a great outcome of your internship would be some precise documentation regarding the guarantees the LLVM dominators give -- possibly also considering classic and weak control dependence and the difference between

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 <<insert bug report here>> Reproduced on Debian and Windows ... On 2.4.x if you execute set.seed(12345) t.1 <- rt(n = 1000, df = 20) set.seed(12345) t.2 <- rt(n = 1000, df = 20, ncp = 0) all.equal(t.1, t.2) ## Not close to true This appears to be due to the fact that in 2.4.x rt is now rt function (n, df, ncp = 0) { if

Hi all, Sorry to bother you with the potentially not too bright question, but since I cannot get it to work, I'll have to ask someone.. I've got this vector: > token [1] sal skal skal bak b_r d_ gal kal l_r n_r pak p_r [13] sal sl_r sn_r spak sp_r st_r s_ bak d_ gal l_r pak [25] p_r sak sl_r sp_r t_ kal n_r s_ st_r sak kal

help(qt) states that: "ncp non-centrality parameter delta; currently except for rt(), only for abs(ncp) <= 37.62" so I would expect that calling qt with non-centrality parameter exceeding 37.62 should fail, instead e.g. calling > mapply(function(x) qt(p = 0.9, df = 55, ncp = x),35:45) gives: [1] 40.21448 41.35293 42.49164 43.68862 44.82945 45.97048 47.11170 48.25310 [9]

Hi all, I have an interesting one - Solaris uses a lot of commands to configure specific items. A simple example is coreadm. In this example: # coreadm -p "/var/core/core_%n_%f_%u_%g_%t_%p" will set the directory and filename to dump core files (with some expansion). The question is - how to get this to run only if the config has changed. I have come up with 2 options, neither of

The function 'pchisq' from the 'stats' library gives a wrong result if the argument equals exactly zero: # Upper tail of central 1-df chi^2 distribution > pchisq(1 , 1, ncp=0, lower.tail = F, log.p = FALSE) [1] 0.3173105 > pchisq(0.5 , 1, ncp=0, lower.tail = F, log.p = FALSE) [1] 0.4795001 > pchisq(0.01 , 1, ncp=0, lower.tail = F, log.p = FALSE) [1]

Bug Description: Problem with the function pf() when the non-centrality parameter is large. Here is a sample command. You should see a smooth line from 0 to about 55, and then the values of pf() go crazy from 55 to 100. ############################ ncp <- seq(0,100,length=200) plot(ncp,pf(5,7,2,ncp=ncp)) ############################ Version: platform = i686-pc-linux-gnu arch = i686 os =

Hello all, Here's my query: Running R 1.6.2 on FreeBSD 5.0, and on WinXP, and I find that the following hangs the process: dchisq(alpha=0.01, df=1, ncp=295) but it does work for ncp < 294.92. Is this general? Best wishes to all, Andrew Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885 6226 University of Idaho E : andrewr at uidaho.edu PO

Full_Name: Jerry W. Lewis Version: 2.6.1 OS: Windows XP Professional Submission from: (NULL) (24.147.191.250) pchisq(0,0,ncp=lambda) returns 0 instead of exp(-lambda/2) pchisq(x,0,ncp=lambda) returns NaN instead of exp(-lambda/2)*(1 + SUM_{r=0}^infty ((lambda/2)^r / r!) pchisq(x, df + 2r)) qchisq(.7,0,ncp=1) returns 1.712252 instead of 0.701297103 qchisq(exp(-1/2),0,ncp=1) returns 1.238938

Recent questions about using plotmath have renewed my interest in this question I want to have expressions take values of variables from the environment. I am able to use expressions, and I am able to use paste to put text and values of variables into plots. But the two things just won't work together. Here is some example code that shows what I mean. plot(NA,xlim=c(0,100),ylim=c(0,100))

hello, I have the following problem setting parameter 'frac' in the sigest function of the kernlab package. ## executing the ?sigest example: library(kernlab) data(spam) srange <- sigest(type~.,data = spam) ## works fine... ## setting 'frac' explicitly ## (in this case even to the default of .25) options(error=recover) srange <- sigest(type~.,data = spam, frac = .25) ##