similar to: how to improve the precison of this calculation?

Hello I have a time-comsuming program which need to simplify, I have tested the annotated program as follow: > #define function which will be call > calsta <- function(c, n=100000) + { + i <- seq(from=0, length=c) + logx <- lchoose(NT-n, CT-i) + lchoose(n, i) + logmax <- max(logx) + logmax + log(sum(exp(logx - logmax))) + } > CT=6000 #assignment to CT >

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

Hi there fellow R-users, Can anyone tell me how to build a prediction interval for a gaussian log-link model for the reponse variable?? I can find the standard error of the predictions but I cant seem to find the prediction interval. Is there a way I can calculate the prediction interval from the standard errors?? Here's the example: logX<-rnorm(100)

Hi all I was playing with termplot(), and came across what appears to be an inconsistency. It would appreciate if someone could enlighten me: > # First, generate some data: > y <- rnorm(100) > x <- runif(length(y),1,2) > # Now find the log of x: > logx <- log(x) > > # Now fit two models that are exactly the same, but specified differently: > m1 <-

Good Evening, I recently purchased an EPYC quantum UPS. I installed NUT on the home assistant by connecting the UPS via USB and tried all the various drivers in the list, the only one that seems to work is: usbhid-ups with this log: s6-rc: info: service s6rc-oneshot-runner: starting s6-rc: info: service s6rc-oneshot-runner successfully started s6-rc: info: service base-addon-banner: starting

>>>>> 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

>>>>> jing hua zhao >>>>> on Mon, 24 Jun 2019 08:51:43 +0000 writes: > Hi All, > Thanks for all your comments which allows me to appreciate more of these in Python and R. > I just came across the matrixStats package, > ## EXAMPLE #1 > lx <- c(1000.01, 1000.02) > y0 <- log(sum(exp(lx))) > print(y0) ## Inf

Hi Jim, Thanks for your help. I'll respond in the same order as you did: 1. Unfortunately, I did "chown" stuff to these created users... Since the other three responses don't seem to be what you're looking for (but that's only my uninformed interpretation), I suppose the problem lies here? Is there a number of files/directories that I should

Hello, I was thinking about what could be going wrong here, and a few ideas pop up: 1) If you installed NUT from packaging, there should have been no need to add OS groups/users manually. There is a valid use-case for running different daemons under different accounts, as long as they talk over network and access same files or UNIX sockets at best by sharing a group for that, but it does need

I've acquired and installed NUT 2.4.1 on a D-Link DNS323 NAS. With exception of Load and Battery Temp readings all works well. A upsc ups at localhost command returns; battery.charge: 100 battery.charge.low: 10 battery.charge.warning: 50 battery.date: 2001/09/25 battery.mfr.date: 2008/06/05 battery.runtime: 2122 battery.runtime.low: 120 battery.temperature: 3022999999999998800 battery.type:

Hi, I am trying to write the Realized GARCH model with order (1,1) The model can be describe bellow: r_t = sqrt( h_t) * z_t logh_t = w + b*logh_(t-1) + r*logx_(t-1) logx_t = c + q*logh_t + t1*z_t +t2*(z_t ^2 -1) + u_t and z follow N(0,1) , u follow N(0, sigma.u^2) But I'm troubled with the simulation check for my code. After I simulate data from the model and estimate the data, I

Hello i tried to connect my netys 2000 pr ups to ubuntu 11.10 and i have a problem connecting it. After readin a few post i realized to dianosse the connection. I need help resolving the connextion issue So here is the response to??/lib/nut/usbhid-ups -u root -DDDDD -a netys: Network UPS Tools - Generic HID driver 0.35 (2.6.1) USB communication driver 0.31 ? ?0.000000 ? ? send_to_all: SETINFO

Hi, I have been trying to use the function cochran.test from the Outliers package to test for homogeneity of variance. This works well except when I use transformed data. Would anyone have an idea why it doesn't work and how I could do the cochran test on transformed data? Thanks, Stephanie >library(outliers) > set.seed(1234) > x=rnorm(100) >

Dear R-users, I am using R version 2.10.1 under windows. In a barplot, I want to mark one of the bars with a special border color. For example: barplot(c(3, 7, 11), border = c(NA, "red", NA)) But how to do this when the bars are stacked? for example: barplot(matrix(1:6, ncol=3)) # border of second bar (i.e. the one with total height = 7) should be red again, I try: barplot(matrix(1:6,

I'm running my script using mpirun -mp 4 and using snowfall+Rmpi on Linux 64bits. I receive the following error, but apparently without consequences on the results. Any idea? I'm able to reproduce it with a minimal script (below). Seems the critical issue is the for loop. Without it no error. Thanks for your help! TERM: Undefined variable. TERM: Undefined variable. TERM: Undefined

There seems to be a minor bug in barplot.default when used with log scale w= here one or more values is NA: dat <- matrix(1:25, 5) dat[2,3] <- NA barplot(dat, beside =3D T) #Plots and appropriate barplot with gaps for m= issing data barplot(dat, beside =3D T, log =3D "y") #Error in if (min(height + offset) <=3D 0) stop("log scale error: at least = one 'height +

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

Windows 7 Pro x64, NUT 2.6.5-4 (interim release) Product: Back-UPS RS 1200 FW:8.g3 .D USB FW:g3 Setting UPS values can be confusing. For example, battery.charge.low and battery.runtime.low. Using upsrw, the values will be retained after restarting the OS, but not if the UPS is turned off/restarted. In the driver log (below), it looks like the values are obtained from the UPS, but if I set

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 them. /* Compute the log of a sum or difference from logs of terms, i.e., * * log (exp (logx) + exp (logy)) * or log (exp (logx) - exp (logy)) * * without causing overflows or throwing away too much accuracy: */ double Rf_logspace_add(double

Hi All, Thanks for all your comments which allows me to appreciate more of these in Python and R. I just came across the matrixStats package, ## EXAMPLE #1 lx <- c(1000.01, 1000.02) y0 <- log(sum(exp(lx))) print(y0) ## Inf y1 <- logSumExp(lx) print(y1) ## 1000.708 and > ly <- lx*100000 > ly [1] 100001000 100002000 > y1 <- logSumExp(ly) > print(y1) [1] 100002000