similar to: logsumexp function in R

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

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.

Hello All, Want very much to learn how to plot patient drug timelines. Trouble is I need to figure out how to do this today. So not much time for me to struggle with it. Hoping someone can just help me out a bit. Below are some sample data and code that produces what I think is the beginning of a very nice graph. Need to alter the code to: 1. Get the lines for the drugs to appear on the

Hello I want to calculate natural logarithm of sum of combinations as follow: (R code) { com_sum=choose(2000000,482)*choose(1000000,118)+choose(2000000,483)*choose(1000000,117)+...+choose(2000000,i)*choose(1000000,600-i)+...+choose(2000000,600)*choose(1000000,0) #calculate the sum result=log(com_sum) #calculate the log of the sum } But

PLEASE HELP I actually want to do the following: a[j] = (1/(j!))*Π (i-1-d), j = 500, Π means product i = 1 to j   Yet, j! will stop at 170 and Π (i-1-d) at 172; so, a[j] will not exceed 170. I would like to have at least 200 a[j].   WHAT SHOULD I DO?   PLEASE SEE MY CODE FOR DETAIL!! #################################################### R CODE:

Hi all, I'm trying to figure out the effective differences between BFGS and L-BFGS-B are, besides the obvious that L-BFGS-B should be using a lot less memory, and the user can provide box constraints. 1) Why would you ever want to use BFGS, if L-BFGS-B does the same thing but use less memory? 2) If i'm optimizing with respect to a variable x that must be non-negative, a common approach

Hi, I have a data frame with one column containing string of the form "ABC...|XYZ..." where ABC etc are fields of 6 alphanumeric characters each and XYZ etc are fields of 8 alphanumeric characters each; "|" is a mandatory separator; I do not know in advance how many fields of each kind will each row contain. I need to extract these fields from the string. === How do I do that?

I agree with many the sentiments about the wisdom of computing very small p-values (although the example below may win some kind of a prize: I've seen people talking about p-values of the order of 10^(-2000), but never 10^(-(10^8)) !). That said, there are a several tricks for getting more reasonable sums of very small probabilities. The first is to scale the p-values by dividing the

Hello all, I was wondering if there is an R function to do the following: [*] log(pnorm(x)-pnorm(y)), where x>y. I don't want all the area under the natural log of the normal pdf less than x, I only want the area between y and x. I am aware of the ability to specify log.p=TRUE, which gives me the log of the probability that X<=x. This does not help me, because the following code:

dear list I use runif to generate a ramdom number between min and max runif(n, min=0, max=1) however , the syntaxe of rexp does not allow that rexp(n, rate = 1) and it generate a number with the corresponding rate. The question is: how to generate a number between min and max using rexp(). Regards -- PhD candidate in Computer Science Address 3 avenue lamine, cité ezzahra, Sousse 4000

>>>>> William Dunlap via R-devel >>>>> on Sun, 23 Jun 2019 10:34:47 -0700 writes: >>>>> William Dunlap via R-devel >>>>> on Sun, 23 Jun 2019 10:34:47 -0700 writes: > include/Rmath.h declares a set of 'logspace' functions for use at the C > level. I don't think there are core R functions that call

Dear R developers, I am using R under Linux, but I would like to share an extension package with some Windows users. The package contains only data and .R scripts. There is no src directory. So, I think I do not need a Windows machine with C compiler, "make", "sh" and "perl". If I am wrong, please tell me. I tried the following approaches (after verifying the

You may want to look into using the log option to qnorm e.g., in round figures: > log(1e-300) [1] -690.7755 > qnorm(-691, log=TRUE) [1] -37.05315 > exp(37^2/2) [1] 1.881797e+297 > exp(-37^2/2) [1] 5.314068e-298 Notice that floating point representation cuts out at 1e+/-308 or so. If you want to go outside that range, you may need explicit manipulation of the log values. qnorm()

In R-2.10.0, the development version, function as.factor() uses 17 digit precision for conversion of numeric values to character type. This is very good for the consistency of the resulting factor, however, i expect that people will complain about, for example, as.factor(0.3) being [1] 0.29999999999999999 Levels: 0.29999999999999999 I suggest to extend the "Warning" section of

Hello All, My algorithm as follows; y <- c(1,1,1,0,0,1,0,1,0,0) x <- c(1,0,0,1,1,0,0,1,1,0) n <- length(x) t <- matrix(cbind(y,x), ncol=2) z = x+y for(j in 1:length(x)) { out <- vector("list", ) for(i in 1:10) { t.s <- t[sample(n,n,replace=T),] y.s <- t.s[,1] x.s <- t.s[,2] z.s <- y.s+x.s out[[i]] <- list(ff <- (z.s), finding=any (y.s==y[j])) kk

List members, Via searches I've seen similar discussion of this topic but have not seen resolution of the particular issue I am experiencing. If my search on this topic failed, I apologize for the redundancy. I am attempting to generate random covariance matrices but would like the corresponding correlations to be uniformly distributed between -1 and 1. The approach I have been using is:

Hi all, I'm interested in doing a dot plot where *both* the size and color (more specifically, shade of grey) change with the associated value. I've found examples online for ggplot2 where you can scale the size of the dot with a value: http://had.co.nz/ggplot2/graphics/6a053f23cf5bdfe5155ab53d345a5e0b.png Or scale the color with the value:

foo <- rnorm(30*34*12) dim(foo) <- c(30, 34, 12) I want to make a data.frame out of this three-dimensional array. Each dimension will be a variabel (column) in the data.frame. I know how this can be done in a very slow way using for loops, like this: x <- rep(seq(from = 1, to = 30), 34) y <- as.vector(sapply(1:34, function(x) {rep(x, 30)})) month <- as.vector(sapply(1:12,

Dear all, I have question but cannot explain without providing some context first: I want to calculate how many policy-connected coalitions between 7 parties are possible. I have positions on an one-dimensional scale for each party and I have sorted the parties on the positions (it is sorted from extreme left to extreme right, hence using a left-right scale). A policy-connected coalition

In looking at rootfinding for the histoRicalg project (see gitlab.com/nashjc/histoRicalg), I thought I would check how uniroot() solves some problems. The following short example ff <- function(x){ exp(0.5*x) - 2 } ff(2) ff(1) uniroot(ff, 0, 10) uniroot(ff, c(0, 10), trace=1) uniroot(ff, c(0, 10), trace=TRUE) shows that the trace parameter, as described in the Rd file, does not seem to be