similar to: Is there an exact binomial k-sample test of equivalence?

require(ppls) data(BOD) X<-BOD[,1] y<-BOD[,2] Xtest=seq(min(X),max(X),length=200) dummy<-X2s(X,Xtest,deg=3,nknot=20) Z<-dummy$Z Ztest<-dummy$Ztest size<-dummy$sizeZ P<-Penalty.matrix(size,order=2) lambda<-200 number.comp<-3 penalized.pls(Z,y,P=lambda*P,ncomp=number.comp)$coefficients # By default kernel=F

Hi, I don't know how to sample such data, it can't be done by row sampling as default method on matrix in boot. Function takes matrix and returns single coefficient. #There is a macro but I want use R :) http://www.comm.ohio-state.edu/ahayes/SPSS%20programs/kalphav2_1.SPS library(concord) library(boot) # The data are rates among observers with NA's

Hi Is there a program which allow me to see how "my" traffic goes through my iptables rules? Which accept it, which deny? Right now my router has a little bit of traffic and its hard to see only mine traffic. -- Miłego Dnia Krystian Antoni _______________________________________________ LARTC mailing list LARTC@mailman.ds9a.nl http://mailman.ds9a.nl/cgi-bin/mailman/listinfo/lartc

I am trying to do a power analysis to get the number of replicas per treatment. If I try to get the power it works just fine: setn=c(2,3) sdx=c(1.19,4.35) power.t.test(n = setn, delta = 13.5, sd = sdx, sig.level = 0.05,power = NULL) If I go the other way to obtain the "n" I have problems. sdx=c(1.19,4.35) pow=c(.8,.8) power.t.test(n = NULL, delta = 13.5, sd = sdx, sig.level = 0.05,

Everyone, I'm very new to R, especially when it comes to loops and functions, so please bear with me if this is an elementary question. I cannot seem to figure out how to construct a loop which runs a function until a certain value is computed. For example, say I have the following: num = numeric (10) num [1] = 0 for (i in 2:10) { num [i] = num [i-1] + 5 } This adds 5 to the

What are some effective ways to leverage the strengths of R and Mathematica for the analysis of a single data set? More specifically, are there any functions that can assist with any of the following? 1. Calling an R function from Mathematica. 2. Calling a Mathematica function from R. 3. Using XML or another reliable data format to pass vectors, matrices, and/or lists from one environment to

Hello all, I had a very strange looking problem that turned out to be due to unexpected (by me at least) format changes to one of my data files. We have a small lab study in which each run is represented by a row in a tab-delimited file; each row identifies a repetition of the experiment and associates it with some subjective measurements and times from our notes that get used to index another

Hi Couple months ago I started to have a strange problem with HTB. My setup is Fedora Core 2 + Pentium 2 233 + 128 MB of ram and its serving as a router. For some time since going to kernel 2.6 my HTB QoS Stalls for couple seconds, every couple minutes. If the connection load is bigger the stalling is more frequent and takes longer. I isolated the problem to be with HTB (CBQ works fine). The

Hi all, In the course of ongoing improvement of plotrix, I was alerted to the fact that setting, e.g.: par(font.lab=3, font.axis=3) only seems to work for "plot" (and maybe other functions), but not for "axis". par(font=3) works for everything (except the title, which is probably specified separately), but there are probably situations in which someone doesn't want

Hello everyone, I will like to know if there is an R package to compute exact confidence intervals for the ratio of two binomial proportions. Tony. [[alternative HTML version deleted]]

I am announcing the release of the exactci package. It calculates exact tests and confidence intervals for binomial and Poisson tests. Here is an example to motivate the package: Suppose you want to see if the observed rates of 2/17877 for group A are significantly different from the observed rates of 10/20000 for group B assuming Poisson counts. The poisson.test function in the stats package

I am announcing the release of the exactci package. It calculates exact tests and confidence intervals for binomial and Poisson tests. Here is an example to motivate the package: Suppose you want to see if the observed rates of 2/17877 for group A are significantly different from the observed rates of 10/20000 for group B assuming Poisson counts. The poisson.test function in the stats package

Dear R developers, I have noticed a discrepancy between the coefficients returned by R's glm() for logistic regression and SAS's PROC LOGISTIC. I am using dist = binomial and link = logit for both R and SAS. I believe R uses IRLS whereas SAS uses Fisher's scoring, but the difference is something like 100 SE on the intercept. What accounts for such a huge difference? Thank you for

Dear List Members, I am in the process of designing a study examining pay and performance in Major League Baseball across several seasons, and before I get too deeply into it, I'd like to ask whether the group members think that performance across seasons is independent, or if it needs to be treated like a time-series variable so that lack of independence can be controlled. Any ideas or

I'm trying to compute sample size requirements for a binomial exact test. we want to show that the proportion is at least 90% assuming that it is 95%, with 80% power so any asymptotic approximations are out of the questions. I was planning on using binom.test to perform the simple test against a prespecified value, but cannot find any functions for computing sample size. do any exist?

When I try to apply mean to a list, I get the answer : argument is not numeric or logical: returning NA Could you help me? (I am a very beginner) -- View this message in context: http://r.789695.n4.nabble.com/mean-tp4674999.html Sent from the R help mailing list archive at Nabble.com.

I'm having trouble to do an infinite sum in R I want to do the infinite sum of 1/(1+n) how would I do this in R? Thank You -- View this message in context: http://r.789695.n4.nabble.com/How-to-do-an-infinite-sum-in-R-tp4649770.html Sent from the R help mailing list archive at Nabble.com.

Dear R Users, Is the p-value reported in a two-tailed binomial exact test in error or is it a feature? If it is a feature, could someone provide a reference for its two-tailed p-value computations? Using Blaker's (2000 - Canad. J. Statist 28: 783-798) approach,the p-value is the minimum of the two-tailed probabilities $P \left(Y\geq y_{obs}\right)$ and $P\left(Y\leq y_{obs}\right)$

Hi all, What's the equivalent to length(unique(x)) == 1 if want to ignore small floating point differences? Should I look at diff(range(x)) or sd(x) or something else? What cut off should I use? If it helps to be explicit, I'm interested in detecting when a vector is constant for the purpose of visual display. In other words, if I rescale x to [0, 1] do I have enough precision to get

Hi, Are there any special statistical tests, or functions in R I could use to measure "cone-like" distributions? I have several data-sets, which I've been plotting parts of as 2D plots, where I get a "cone-like" distribution of the data points. That is, the data appears to be bounded by two non-parallel lines, starting at the origin, giving rise to a