similar to: Can simulation involving random number generation be segm ented?

Hello, This is my first post to the help request list, so I'm going to err on the side of giving too much information. I'm working on writing a simulation in which agents will make repeated production and exchange decisions with randomly chosen partners. The idea is, all agents can produce two goods which they want to consume, they choose a value t in [0,10] which sets their production

> From: Hin-Tak Leung > > Izmirlian, Grant (NIH/NCI) wrote: > <snipped> > > The only interesting feature is that the tree structure has been > > implemented in C. Its a neater way to carry stuff around and I am > > guessing would make future implementation easier. > > > > Because of its inherent redundancy from the users standpoint, it > >

------------------------------ On Sat, May 16, 2015 2:33 PM BST Marc Schwartz wrote: > >> On May 16, 2015, at 6:11 AM, Hin-Tak Leung <htl10 at users.sourceforge.net> wrote: >> >> >> >> ------------------------------ >> On Sat, May 16, 2015 8:04 AM BST Uwe Ligges wrote: >> >> Not sure why this goes to R-devel. You just could have asked

Hi, list I am doing 100,000 iterations of Bayesian simulations. What I did is I split it into 4 different R sessions, each one runs 25,000 iteration. But two of the sessions gave the simulation result. I did not use any set.seed(). What is going on here? Thanks, Mike [[alternative HTML version deleted]]

On Mon, 2005-10-24 at 17:14 +0100, Hin-Tak Leung wrote: > Peter Dalgaard wrote: > > hin-tak.leung at cimr.cam.ac.uk writes: > > > > > >>Full_Name: Hin-Tak Leung > >>Version: R 2.2.0 > >>OS: x86 linux > >>Submission from: (NULL) (131.111.126.242) > >> > >> > >>Rgnome depends libglade 0.x and libxml 1.x . >

Hi, I am testing code that is working successfully using constrOptim. I am replacing constrOptim with other solvers to compare benefits and performance. My belief was that, like constrOptim, auglag in the alabama package would eliminate beta vectors that failed the constraints prior to calling the objective function. These betas are not only not in the solution space but also cause

------------------------------ On Sat, May 16, 2015 8:04 AM BST Uwe Ligges wrote: >Not sure why this goes to R-devel. You just could have asked the >maintainer. Terry Therneau is aware of it and promised he will fix it. > The quickest fix is to add cmprsk to the recommended list , and that's is an R-devel issue. >On 16.05.2015 07:22, Hin-Tak Leung wrote: >> 'make

Exactly! Thanks, Duncan. Let me re-phrase me question like this: 1) X_i values are independent Gammas, with the shape 0.067 and scale 0.008 2) Min(X)=1 and Max(X)=85 3) SUM(X)=2000 4) Do I also have to define the number of draws? if yes, it could be 250. Based on these restrictions, I want to generate random draw. I'm wondering how I can do this in R. Thanks. Garry On Tue, Nov 10, 2009

Greetings, I have a simulation of a nonlinear model that is failing. But it does not fail til way into the simulation. I would like to look at the run that is failing and maybe I could if I could capture the seed for the failing run. The help file on set.seed says you can do it but when I tried rs<-.Random.seed print(paste("rs",rs,sep=" ")) I got 626 of them so I

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Dear R community,and especially Giovanni Millo, For my master's thesis i need to simulate a panel data with the fixed effects correlated with the predicor, so i run the the following code: set.seed(1970) #######################Panel data simulation with alphai correlated with xi##################################### n <- 5 t <- 4 nt <- n*t pData <- data.frame(id =

Hello, Right. Missed that one. Rui Barradas Enviado a partir do meu smartphone Samsung Galaxy.-------- Mensagem original --------De: Eric Berger <ericjberger at gmail.com> Data: 30/01/2018 10:12 (GMT+00:00) Para: Rui Barradas <ruipbarradas at sapo.pt> Cc: Daniel Nordlund <djnordlund at gmail.com>, smart hendsome <putra_autumn86 at yahoo.com>, r-help at r-project.org

SUSE 9.1 samba-3.0.9-2.6 samba-client-3.0.9-2.6 I am getting some errors that I can't seem to track down in any of the archives. I came across this problem when trying to delete a driver none of the printers are listed in the smb.conf - it is all being generated from the cups and the printcap that cups makes on load First enumprinters works: rpcclient $> enumprinters

On 2nd thought, I think a better fix to the segfault is something like this: --- a/src/main/memory.c +++ b/src/main/memory.c @@ -3444,6 +3444,8 @@ R_xlen_t (XTRUELENGTH)(SEXP x) { return XTRUELENGTH(CHK2(x)); } int (IS_LONG_VEC)(SEXP x) { return IS_LONG_VEC(CHK2(x)); } const char *(R_CHAR)(SEXP x) { + if(!x) + error("de-referncing null. Check the validity of your data.");

Hi this is my first post. I am trying to run a simulation for a computer playing Von Neumann poker and adjusting it's expectation of an opponent's behavior according to how the opponent plays. This program involves random generation of "hands" and shifting of parameters. However, when I run the code, no errors come up, but the program doesn't do anything. Could someone

Hi all, I am running a simulation and a curious error keeps coming up that stops the whole process. The error is a subscript out of bounds error, and it seems to happen at different points (floating around) throughout the looping simulation. Say, for example, it crashes on sample 1 - iteration 200. I can force it to start again on iteration 202 with all of the same settings, and it is

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Hi Jeem, First, please send questions like this to the help list, not me. I assume that you are in a similar position to sjtan who has been sending almost exactly the same questions. The problem is not in the loops (which look rather familiar to me) but in your initial assignments at the top. For instance: scale parameter=(1,1.5,2,2.5,3) produces an error which has nothing to do with the

When I try to create a Rasch simulation of data using the sim.rasch function, I get more items than I intend #My code library(eRm) #Number of items k <- 20 #Number of participants n <- 100 #Create Rasch Data #sim.rasch(persons, items, seed = NULL, cutpoint = "randomized") r.simulation <- sim.rasch(n,k) I end up with 20 participants and 100 items, but the instructions say