similar to: Problem with dgamma function.

Hi All, Here 's what I got using dgamma function : > nu<-.2 > nu*log(nu)-log(gamma(nu))+(nu-1)*log(1)-nu*(1) [1] -2.045951 > dgamma(1,nu,nu,1) [1] 0.0801333 > dgamma(1,nu,nu,0) [1] NaN Warning message: NaNs produced in: dgamma(x, shape, scale, log) Could anyone tell me what is wrong here ? I am using R-2.4.1 on windows XP. Thanks a lot.

Dear R-Devel group, My name is Alexey, a data scientist from Moscow, currently working for Align Technology Inc. We have recently had a discussion of the results that the dgamma function (stats) returns for an extreme point (x == 0). <dgamma(0,1,1,log = FALSE) [1] 1 and <dgamma(0,0.5,1,log = FALSE) [1] Inf Density appears to be defined in point zero for the distribution with the

I define priors in jags within r using a gamma distribution. I would like to control the shape but I have problems. Any help will be usefull. From help of dgamma ___________________ The Gamma distribution with parameters shape = a and scale = s has density f(x)= 1/(s^a Gamma(a)) x^(a-1) e^-(x/s) and rate=1/scale From jags user manual ____________________ dgamma(r, mu) has a density of

Hello, In WinBUGS 1.4 manual (http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/manual14.pdf), the gamma density is presented as dgamma(r,mu) where r and mu are the shape and rate parameters, respectively. In JAGS (rjags) manual version 1.0.2, May 9, 2008 (http://www-fis.iarc.fr/~martyn/software/jags/jags_user_manual.pdf), on page 26 the gamma density is presented as dgamma(mu,r) instead of dgamma(r,mu).

Can someone explain to me in what way the new (dpqr)gamma parameter can be interpreted as a rate (when shape != 1)? The only gamma rate that I am aware of is the hazard rate given by dgamma/(1-pgamma), the log of which is returned by my hgamma function (event library). Jim -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi all I have a couple of obscure questions for R/Splus experts (which unfortunately isn't me!) I am trying to compute Bayes Factors using some Splus code of Raftery in Gilks et al (1996). Only problem is 1) R doesn't seem to have a robust covariance (cov.mve) which I suspect I need rather than a non-robust classical estimate 2) Splus has cov.mve BUT dgamma in Splus doesn't have a

There's an apparent inconsistency between the behavior of d(pqr)gamma and other distribution functions for "bad" parameter values. Specifically, most distributions give NaN and a warning for bad parameters (e.g. probabilities <0 or >1). In contrast, d(pqr)gamma actually gives an error and stops when shape<0. I don't see why it has to be this way -- the internal C code

Hi, In src/nmath/dgamma.c the comment at the top says * DESCRIPTION * * Computes the density of the gamma distribution, * * 1/s (x/s)^{a-1} exp(-x/s) * p(x;a,s) = ----------------------- * (a-1)! * * where `s' is the scale (= 1/lambda in other parametrizations) * and `a' is the shape parameter ( = alpha in

Just to close the thread. The problem was that I was using an old version of the code. If anyone has the same problem, you can download the code from here: http://www.thetechguide.com/howto/asterisk/bluetoothfiles.tar.gz Good luck, Danko ----- Original Message ----- From: "Danko Miocevic" <danko@santirso.com.ar> To: "Asterisk

Where can I get some asterisk books.. or tutorials..? I?ve been searching in google.. but I find just some tutorials explaining how to fast set up an asterisk server. I want to learn how to use it and how to make my own configurations. So, the thing is that I want to know what is the best book or tutorial that you know? recomendations? Thanks to everyone... Danko Miocevic

Hello, I?m trying to use my phone with asterisk to get GSM connectivity but I can?t compile the code. I got the asterisk, chan_bluetooth, zaptel and libpri sources, the last two ones compiled perfectly. I have added this to the /usr/src/asterisk/channels/Makefile: include /usr/src/chan_bluetooth/Makefile and I?ve also added chan_bluetooth.so to the CHANNEL_LIBS var. When I do "make

Hello, Quick question. I have written a C function - I would like to make it return two vectors to the R environment - one STRSXP vector, and one INTSXP vector. Is this possible/ easy to do using the API? I looked, but could not find the answer to this question in the "Writing R Extensions" guide. Thanks very much for your help! Charles [[alternative HTML version deleted]]

Hi, Trying to decrease the size of a SEXP variable without reassigning values individually in a loop. So far, I've tried using Realloc, as the follow source demonstrates: SEXP dothis() { SEXP Rblah; PROTECT(Rblah = NEW_INTEGER(6)); int* blah = INTEGER(Rblah); blah[0] = 1; blah[1] = 2; blah[2] = 3; Realloc(Rblah, 3, INTEGER); UNPROTECT(1); return(Rblah); } According to the

cbind/ rbind/ data.frame functions are very convenient for merging vectors of different types into a single data frame, but take quite a bit of time to execute on larger data sets. Is it possible to speed these up a bit? What functions do you use instead? Thanks & regards, Charles

Dear R-devel, I am writing a package that needs some C++ functions from an external SDK (Affymetrix fusion). The same functions are already compiled into another package (affxparser). Can I dynamically link to the compiled code in affxparser, rather than re-compiling these separately into my package? Not a lot of experience on this subject! Thanks, Charles

Hello everyone, I was trying to do some distribution fitting with a numerical field called Tolls. The sample size = 999 rows. Basically I assigned the Toll data to a new variable K by doing: k<-dtest$Toll After that, tried to fit a gamma distribution by doing: fitG<-fitdist(k, "gamma") Then the following messages showed (oh and I checked for empty rows before doing this):

Hello everyone, With th bar histogram (number of occurrences) hist<-c(24,7,4,1,2,1,1) of seven equally spaces classes ]1-4], ]5-8], ]9-12], ]13-16], ]17-20], ]21-24], ]25-28], I obtained shape=0.8276 and rate=0.1448. I would like to know how to build the continuous pdf of a this gamma distribution knowing these two estimated parameters such that I will be able to predict the pdf of any

I want to create a grid of function values for use in `contour' or `persp'. The function is the log-likelihood for the gamma. The sample is stored as vector of length 20 called `Survival'. A single evaluation of the log-likelihood at, say, scale = 9 and shape = 10 would be obtained by sum(dgamma(Survival, scale = 9, shape = 10, log = TRUE)) (This may work only 0.99.0, I'm not

Hi, How can I convert the matrices to list. For example I have this snippet: samples<-mymatrix[1,] print(samples) which prints: V1 V2 V3 V4 V5 V6 1 103.9 88.5 242.9 206.6 175.7 164.4 How can I convert the object "samples" such that it prints: [1] 103.9 88.5 242.9 206.6 175.7 164.4 The reason I ask this because I can't use the former "samples"

Dear R Users, I am trying to obtain a best-fit analytic distribution for a dataset with 11535459 entries. The data range in value from 1 to 300000000. I use: fitdistr(data, "gamma") to obtain mle's for the parameters. I get the following error: Error in optim(start, mylogfn, x = x, hessian = TRUE, ...) : non-finite finite-difference value [1] And the following warnings: