similar to: non-centrality parameter in pf() (PR#752)

(1) ...need to speed up a monte-carlo sampling...any suggestions about how I can get R to use all 8 cores of a mac pro would be most useful and very appreciated... (2) spent the last few hours trying to get pnmath to compile under os- x 10.5.4... using gcc version 4.2.1 (Apple Inc. build 5553) as downloaded from CRAN, xcode 3.0... ...xcode 3.1 installed over top of above after

Hi, I've written some C code for density evaluation of the non-central t distribution. It works with the R-1.7.1 source code if placed in the src/nmath directory and after appropriate changes are made to Makefiles, to the dt function in src/library/base/R/distn.R etc. I haven't read a lot of R source code so it may need some R-ification, but I've tried to use the dt.c file as a

Hi R-devels, I noticed that for the scheduled R 2.3.0, there is still no function df() for non-centrality != 0. Easter is quickly approaching, so as my little gift, I would like to offer you some code to fill this gap: After excluding some "unusual" cases, it amounts to differentiating the corresponding function pnf() --- which in turn leads to the function dnbeta() already available

Hi Folks, I note that, while the "chisq" functions dchisq(x, df, ncp=0, log = FALSE) pchisq(q, df, ncp=0, lower.tail = TRUE, log.p = FALSE) qchisq(p, df, ncp=0, lower.tail = TRUE, log.p = FALSE) rchisq(n, df, ncp=0) all have a slot for the non-centrality parameter "ncp", of the functions for the t and F distributions: dt(x, df, log = FALSE)

On a recent FreeBSD 8.0-CURRENT (i386) building R (any version) breaks with the following messages: ---------------------------------------------------------------------- [...snip...] gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c wilcox.c -o wilcox.o gcc -std=gnu99 -I. -I../../src/include -I../../src/include -I/usr/local/include

Hello Everybody, Is there a function available for calculating the density of a non-central t distribution? (dt does not accept the ncp option). Thanks in advance! -- Wolfgang Viechtbauer "Are you not thinking what I am not thinking?" -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

In the help file for the non-central t, the following appears: ncp: non-centrality parameter delta; currently `ncp <= 37.62'. I assume that this means the ncp cannot exceed 37.62. Is this still the case and is there any plans to increase this restriction? Thanks! Jeff Jeff Morris Design Support Clinical Chemistry R&D Ortho-Clinical Diagnostics email: jmorris6 at ocdus.jnj.com

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]

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

Dear people, I've a problem in doing a power calculation. In Fryer and Nicholson (1993), ICES J. mar. Sci. 50: 161-168 page 164 an example is given with the following characteristics T=5, points in time R=5, replicates Var.within=0.1 q=10, a 10% increase per year The degrees of freedom for the test are calculated as Vl=T*R-2=23 and the non-centrality parameter Dl=4.54. Using this they get a

Hello all. It seems that the pf() function when used with noncentral parameters can behave badly at times. I've included some examples below, but what is happening is that with some combinations of df and ncp parameters, regardless of how large the quantile gets, the same probability value is returned. Upon first glance noncentral values greater than 200 may seem large, but they are in

Hi, How to solve this problem. The following is the code. betabinexch0=function(theta,data) + { + eta=theta[,1] + K=theta[,2] + y=data[,1]; n=data[,2] + N=length(y) + val=0*K; + for (i in 1:N) + val=val+lbeta(K*eta+y[i],K*(1-eta)+n[i]-y[i]) + val=val-N*lbeta(K*eta,K*(1-eta)) + val=val-2*log(1+K)-log(eta)-log(1-eta) + return(val) + } > data(cancermortality) >

Dear all, The help page on the t distribution says: The most used applications are power calculations for t-tests: Let T= (mX - m0) / (S/sqrt(n)) where mX is the `mean' and S the sample standard deviation (`sd') of X_1,X_2,...,X_n which are i.i.d. N(mu,sigma^2). Then T is distributed as non-centrally t with `df'= n-1 degrees of freedom and non-centrality

Full_Name: Mike Meredith Version: 2.3.0 OS: WinXP SP2 Submission from: (NULL) (210.195.228.29) Using dt() with a non-centrality parameter and near-zero values for 'x' results in erratic output. Try this: tst <- c(1e-12, 1e-13, 1e-14, 1e-15, 1e-16, 1e-17, 0) dt(tst,16,1) I get: 0.2381019 0.2385462 0.2296557 0.1851817 0.6288373 3.8163916 (!!) 0.2382217 The 0.238 values are okay,

1. lbeta and beta do not work properly: lbeta returns its first argument and beta gives the lbeta result. In names.c lines 245-6, the codes for these should be 2 and 3 instead of 1 and 2 2. crtl-C does not work (except the first time) on Red Hat elf Linux (which has many many other problems as well) nor on the previous version of Linux for Amiga. It worked on Slackware aout Linux and now works

1. lbeta and beta do not work properly: lbeta returns its first argument and beta gives the lbeta result. In names.c lines 245-6, the codes for these should be 2 and 3 instead of 1 and 2 2. crtl-C does not work (except the first time) on Red Hat elf Linux (which has many many other problems as well) nor on the previous version of Linux for Amiga. It worked on Slackware aout Linux and now works

Greetings all, I'm trying to figure out how to calculate the inverse CDF (i.e. a quantile) for a non-central F distribution. I could put together a quick numerical solver routine using the CDF, but I wonder if there's a function that I've missed that would be more efficient? Thank-you, Andrew Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885

Full_Name: Long Qu Version: 2.3.1 OS: Windows XP Submission from: (NULL) (64.113.93.235) The QQ-plot of two versions of simulating noncentral F-distributed random numbers has quite different scales: > qqplot(rf(1000,2,15,3),qf(runif(1000),2,15,3)) The rf() function reads: > rf function (n, df1, df2, ncp = 0) { if (ncp == 0) .Internal(rf(n, df1, df2)) else rchisq(n, df1,

Dear R list members, I have a question about the proper use of the typsize and fscale arguments to nlm. I use nlm in my sem package to fit general structural-equation models, which entails maximizing a multinormal likelihood with respect to parameters that represent regression coefficients and covariances of variables. The magnitudes of these parameters can be very different. The

Dear R Developers: I have been playing with R, release 2.0.1 for a week now and have detected = that all stat functions related to distribution probabilities have the same= problem: 1.- According to the manual the log.p parameter is always the last one. 2.- When you use the software, the last parameter seems to be lower.tail Example: > pt (1.1, 5) [1] 0.8392746 > pt (1.1, 5, F) [1]