similar to: how to to if a calculation is out range?

Dear R users, I'm trying to carry out monte carlo integration of a posterior density function which is the product of a normal and a gamma distribution. The problem I have is that the density function always returns 0. How can I solve this problem? Here is my code #generate data x1 <- runif(100, min = -10, max = 10) y <- 2 * x1^2 + rnorm(100) # # # # # # # # Model 0 # # # # # # #

Dear R users, I have to calculate gamma functions for negative numbers beyond -171.4. e.x. gamma(-500.4) I got following: > gamma(-170.4) [1] -5.824625e-308 > gamma(-171.4) [1] 0 Warning message: underflow occurred in 'gammafn' I have tried to use a recursion getting values a little futher -180. How could I solve this problem? Thank you beforehand. Chuse.

Dear R-users, Is there an R function to compute the multinomial beta function? That is, the normalizing constant that arises in a Dirichlet distribution. For example, with three parameters the beta function is Beta(n1,n2,n2) = Gamma(n1)*Gamma(n2)*Gamma(n3)/Gamma(n1+n2+n3) Thanks in advance for any assisstance. Regards, Greg [[alternative HTML version deleted]]

I have to calculate some formula like: gamma(x)/(gamma(x+y) and I observed that for relatively big values of x, R returns infinity and so cannot compute the formula. Is it possible to force R to give the real value of gamma(x) instead of Inf ? thanks

Hi, I found the following on Windows 2000/NT R Version 1.9.1 (2004-06-21) (also Version 1.9.0): The S4 group "Math" doesn't work as documented; i.e., "log", "log10", "gamma" and "lgamma" are included in the documentation but don't work. See example code below. Moreover, what about 'genericForPrimitive' which is used in

I am trying to solve the integration equation, for different values of K from 4 to 25, the integration is with respect to u, Here is the equation: gamma(k/2) / ( sqrt(k-1)*gamma((k-1)/2) ) * integrate(f= (1+u^2/k-1)^(-k/2), lower=0, upper= sqrt(a^2*k/(k+1-a^2)) ) = the similar expression as te left hand except k becomes k+1 my code is below, I don't know why R keep telling me the syntax

The following seems very strange: > lgamma(-0.04) [1] 3.243307 > gamma(-0.04) [1] -25.61830 Jim -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Hello, for a frequency modelling problem I want to combine expert knowledge with incoming real-life data (which is not available up to now). The frequency has to be modelled with a poisson distribution. The parameter lambda has to be normal distributed (for certain reasons we did not NOT choose gamma althoug it would make everything easier). I've started with the subsequent two functions to

Hi - I ran into a problem when the argument to gamma function is large. Says, if I do the following: > gamma(17000) [1] Inf Warning message: value out of range in 'gammafn' Is there anyway to get around this or other implementation? Thank you. -rc

Hi, I have a dataset with the binary outcome Y(0,1) and 4 covariates (X1,X@,X#,X$). I am trying to use MCMClogit to model logistic regression using MCMC. I am getting an error where it doesnt identify the covariates ,although its reading in correctly. The dataset is a sample of actual dataset. Below is my code: > ####################### > > > #retreive data > # considering four

Hello R-users, When I didn't know about the internal 'choose' function, I made such function, 'my.choose' below. But when I used them instead of choose(6000,20), they didn't give me any answer. What is the difference between 'choose', 'my.choose1', and 'my.choose2' below? That is, what is behind 'choose' function and what's the problem

Hello all, I was wondering if someone can enlighten me as to the difference between the logLik in R vis-a-vis Stata for a GLM model with the gamma family. Stata calculates the loglikelihood of the model as (in R notation) some equivalent function of -1/scale * sum(Y/mu+log(mu)+(scale-1)*log(Y)+log(scale)+scale*lgamma(1/scale)) where scale (or dispersion) = 1, Y = the response variable, and mu

lgamma(x) and lfactorial(x) are defined to return ln|Gamma(x)| {= log(abs(gamma(x)))} or ln|Gamma(x+1)| respectively. Unfortunately, we haven't chosen the analogous definition for lchoose(). So, currently > lchoose(1/2, 1:10) [1] -0.6931472 -2.0794415 NaN -3.2425924 NaN -3.8869494 [7] NaN -4.3357508 NaN -4.6805913 Warning message: In

> > >From: robert-mcfadden w o2.pl > > >Date: 2008/04/02 Wed AM 09:58:28 CDT > > >To: r-help w r-project.org > > >Subject: [R] Nonlinear equation > > > > hi: you need to give an example and details or > > you won't get much response, if any. Equation e.g. (A, B are known constants): 3log(gamma(x))-log(gamma(x)*gamma(2x))+(x-1)*A+B=0

Good afternoon/morning readers. This is the first time I am trying to run some Bayesian computation in R, and am experiencing a few problems. I am working on a Poisson model for cancer rates which has a conjugate Gamma prior. 1) The first question is precisely how I work out the parameters. #Suppose I assign values to theta with *seq()* *theta<-seq(0,1,len=500)* #Then I try out the

Hello, I was wondering if the functions deriv3(), deriv() etc. could be extended to handle psigamma() and its special cases (digamma(), trigamma() etc.). From the error message it seems that 'psigamma' needs to be added to the derivatives table. This might be easy since psigamma() has a deriv argument. Additionally, this error message is also obtained when requesting for the Hessian of

I am just trying to teach myself how to use the mle function in R because it is much better than what is provided in MATLAB. I am following tutorial material from the internet, however, it gives the following errors, does anybody know what is happening to cause such errors, or does anybody know any better tutorial material on this particular subject. >

I am looking for a method of dealing with the modified Bessel function K_\nu(x) for large \nu. The besselK function implementation of this allows for dealing with large values of x by allowing for exponential scaling, but there is no facility for dealing with large \nu. What would work for me would be an lbesselK function in the manner of lgamma which returned the log of K_\nu(x) for large

Hello I am trying to evaluate an Incomplete gamma function in R. Library Zipfr gives the Igamma function. From Mathematica, I have: "Gamma[a, z] is the incomplete gamma function." In[16]: Gamma[9,11.1] Out[16]: 9000.5 Trying the same in R, I get > Igamma(9,11.1) [1] 31319.5 OR > Igamma(11.1,9) [1] 1300998 I know I have to understand the theory and the math behind it rather

hello all happy new year and hope you r having a good holiday. i would like to calculate the expectation of a particular random variable and would like to approximate it using a number of the functions contained in R. decided to do some experimentation on a trivial example. example ======== suppose x(i)~N(0,s2) where s2 = the variance the prior for s2 = p(s2)~IG(a,b) so the posterior is