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We are happy to announce the first CRAN release of rTRNG version 4.20-1. rTRNG is a package for advanced parallel Random Number Generation in R. It relies on TRNG (Tina?s Random Number Generator, <https://numbercrunch.de/trng/>), a state-of-the-art C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations. In p...

We are happy to announce the first CRAN release of rTRNG version 4.20-1. rTRNG is a package for advanced parallel Random Number Generation in R. It relies on TRNG (Tina?s Random Number Generator, <https://numbercrunch.de/trng/>), a state-of-the-art C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations. In p...

Hi all, I've been curious about using hardware true random number generators in my VM clusters. This got me wondering about the VM's /dev/random source... If I setup a hardware TRNG on the host, would the VM's also benefit from it? Thanks! -- Digimer Papers and Projects: https://alteeve.ca/w/ What if the cure for cancer is trapped in the mind of a person without access to education?

...** I build a neighbours list with spatial weights** nb20.w<-nb2listw(nb20, glist=NULL, style="W", zero.policy=TRUE) **I run a glm** glm1<-glm(matriz$sp~poly(matriz$iso,3)+poly(matriz$tmax,3)+poly(matriz$mdr,3)+poly(matriz$twq,3)+poly(matriz$tmin,3)+poly(matriz$pdq,3)+poly(matriz$trng,3),data=matriz, subset=matriz$casos1>0, family=binomial) glm.scope<-list("var1"=~1+iso+poly(iso,2)+poly(iso,3),"var2"=~1+tmax+poly(tmax,2)+poly(tmax,3),"var3"=~1+mdr+poly(mdr,2)+poly(mdr,3),"var4"=~1+twq+poly(twq,2)+poly(twq,3),"var5"=~1+tmin+...