Doing a web search on
R CRAN GJR GARCH
brought up the rugarch package. The models you mentioned are discussed in
the documentation to that package
https://cran.r-project.org/web/packages/rugarch/vignettes/Introduction_to_the_rugarch_package.pdf
On Mon, Mar 25, 2019 at 2:06 PM Amon kiregu wrot
what is the r code for simulating PowerGARCH,Threshold GARCH,and GJR GARCH
in order to capture heteroscedasticity,volatility clustering,etc,,so that i
can have simulation of mean part and simulation on innovation part.
thanks
[[alternative HTML version deleted]]
_
Hello,
Right. Missed that one.
Rui Barradas
Enviado a partir do meu smartphone Samsung Galaxy. Mensagem original
De: Eric Berger Data: 30/01/2018 10:12
(GMT+00:00) Para: Rui Barradas Cc: Daniel Nordlund
, smart hendsome ,
r-help@r-project.org Assunto: Re: [R] Simulation
Or a shorter version of Rui's approach:
set.seed(2511)# Make the results reproducible
fun <- function(n){
f <- function(){
c(mean(runif(5,1,10)),mean(runif(5,10,20)))
}
replicate(n, f())
}
fun(10)
On Tue, Jan 30, 2018 at 12:03 PM, Rui Barradas wrote:
> Hello,
>
> Another way would
Hello,
Another way would be to use ?replicate and ?colMeans.
set.seed(2511)# Make the results reproducible
fun <- function(n){
f <- function(){
a <- runif(5, 1, 10)
b <- runif(5, 10, 20)
colMeans(cbind(a, b))
}
replicate(n, f())
}
fun(10)
Hope this hel
On 1/29/2018 9:03 PM, smart hendsome via R-help wrote:
Hello everyone,
I have a question regarding simulating based on runif. Let say I have
generated matrix A and B based on runif. Then I find mean for each matrix A and
matrix B. I want this process to be done let say 10 times. Anyone can he
Hello everyone,
I have a question regarding simulating based on runif. Let say I have
generated matrix A and B based on runif. Then I find mean for each matrix A and
matrix B. I want this process to be done let say 10 times. Anyone can help me.
Actually I want make the function that I can pla
On 4/06/16 11:54 AM, tan sj wrote:
Hi, i am student from malaysia, i am new in r programming field, now i am
trying to conduct a robustness study on 2 sample test under several combination
of factors such as sample sizes ,standard deviation ratio and also
distribution..
but now i am stuckin
y
College Station, TX 77840-4352
-Original Message-
From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Kristi Glover
Sent: Wednesday, April 20, 2016 1:06 AM
To: R-help
Subject: [R] simulation in R
I realized that there was a typo error. I mean "Monte Ca
Hi, i am student from malaysia, i am new in r programming field, now i am
trying to conduct a robustness study on 2 sample test under several combination
of factors such as sample sizes ,standard deviation ratio and also
distribution..
but now i am stucking in how to use for loop or apply fun
Before you post on Rhelp you should first read the Posting Guide. It tells you
that requests for statistical advice might be answered but are not really
on-topic. Furthermore requests for tutorials or extended worked examples should
probably be accompanied by evidence of searching using Google o
I have a data from 4 variables ( STOCK, CPI, EXC, and CCI) from 1980 to 2012. I
want to do a forecast using VAR(12) model with a simulation of 100,000 for 5
years. And also estimate the RMSE, MAPE, and Theil Inequality. Can anyone help
me with this problem in R? Thanks so much.
[[alter
Dear all,
I have a strongly balanced panel dataset of 46 entities x11 years.
Observed vars are not normally distributed
How should I simulate the ov ?
I do not know the distribution
Can somebody pl help
--
**
*Deva*
[[alternative HTML version deleted]]
Dear all,
I have a strongly balanced panel dataset of 46 entities x11 years.
Observed vars are not normally distributed
How should I simulate the ov ?
I do not know the distribution
Can somebody pl help
--T&R ... Deva,
[[alternative HTML version deleted]]
PLZ mke sure the package installed which contains "mvrnorm" function.
--
PO SU
mail: desolato...@163.com
Majored in Statistics from SJTU
At 2014-09-14 09:56:34, "thanoon younis" wrote:
>Dear R members
>I want to simulate data depending on SEM and when i applied the code below
>i found
Adding back the list address:
On Sep 14, 2014, at 9:53 AM, thanoon younis wrote:
> thank you for your help but i still have error after putting semicolon
> "Error: unexpected symbol in:
> "Ro<-matrix(data=c(7.0,2.1,2.1,7.0), ncol=2)
> yo<-matrix(data=NA,nrow=N,ncol=P) p""
The error message sho
On Sep 14, 2014, at 8:48 AM, Don McKenzie wrote:
ccing to list, as requested in the posting guide, so that others
may be able to help you.
On Sep 14, 2014, at 8:45 AM, thanoon younis > wrote:
Thank you very much for your reply
the output is
#Do simulation for 100 replications
N<-1000;
cc�ing to list, as requested in the posting guide, so that others may be able
to help you.
On Sep 14, 2014, at 8:45 AM, thanoon younis wrote:
> Thank you very much for your reply
>
> the output is
>
> > #Do simulation for 100 replications
> > N<-1000; P<-10
> >
> > phi<-matrix(data=c(1.0,0.3
What errors? What is your output? What output did you expect?
On Sep 14, 2014, at 6:56 AM, thanoon younis wrote:
> Dear R members
> I want to simulate data depending on SEM and when i applied the code below
> i found some errors and i still cannot run it.
> many thanks in advance
>
>
> Thano
Dear R members
I want to simulate data depending on SEM and when i applied the code below
i found some errors and i still cannot run it.
many thanks in advance
Thanoon
#Do simulation for 100 replications
N<-1000; P<-10
phi<-matrix(data=c(1.0,0.3,0.3,1.0),ncol=2) #The covariance matrix of xi
Ro<
dear all members
i am trying to simulate data with mixed ordered categorical and
dichotomous variables with 200 observation and 10 var. 5 ordered
categorical and 5 dichotomous and i want to put a high correlation between
variables so i must find correlation between dichotomous and the
correlation
dear all members
i have a problem with the code below, my problem in this code i want to put
a high correlation between variables in group R1 and also put a high
correlation between variables in group R2. after checking the correlation
between variables in R1 also between variables in R2 i didn't f
Dear Thanoon,
You might look at the various item simulation functions in the psych package.
In particular, for your problem:
R1 <- sim.irt(10,1000,a=3,low = -2, high=2)
R2 <- sim.irt(10,1000,a=3,low = -2, high=2)
R12 <- data.frame(R1$items,R2$items)
#this gives you 20 items, grouped with high c
Dear R-users
i need your help to solve my problem in the code below, i want to simulate
two different samples R1 and R2 and each sample has 10 variables and 1000
observations so i want to simulate a data with high correlation between
var. in R1 and also in R2 and no correlation between R1 and R2 a
Please remember the 'reply all' for the r-help page.
First Question: How can i use Pearson correlation with dichotomous data? i
want to use a correlation between dichotomous variables like spearman
correlation in ordered categorical variables?
cor(variable1, variable2, *method = "pearson"*)
Seco
Thanoon,
You should still send the question to the R help list even when I helped
you with the code you are currently using. I will not always know the best
way or even how to proceed with some questions. As for to your question
with the code below.
Firstly, there is no 'phi' method for cor in
Thanoon,
My reply to your previous post should be more than enough for you to
accomplish your goal. Please look over that script again:
ords <- seq(4)
p <- 10
N <- 1000
percent_change <- 0.9
R <- as.data.frame(replicate(p, sample(ords, N, replace = T)))
or alternatively as Mr. Barradas suggest
Hello,
At an R prompt type
?rbinom
?replicate
Hope this helps,
Rui Barradas
Em 10-04-2014 02:28, thanoon younis escreveu:
hi
i want to simulate multivariate dichotomous data matrix with categories
(0,1) and n=1000 and p=10.
thanks alot in advance
[[alternative HTML version deleted
On 10/04/14 09:28, thanoon younis wrote:
hi
i want to simulate multivariate dichotomous data matrix with categories
(0,1) and n=1000 and p=10.
Nobody's stopping you! :-)
cheers,
Rolf Turner
__
R-help@r-project.org mailing list
https://stat.ethz.ch
hi
i want to simulate multivariate dichotomous data matrix with categories
(0,1) and n=1000 and p=10.
thanks alot in advance
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
Thanoon,
Firstly, please remember to reply to the R help list as well so that other
may benefit from your questions as well.
Regarding your second request, I have written the following as a very naive
way of inducing correlations. Hopefully this makes it perfectly clear what
you change for diffe
Hi Thanoon,
How about this?
# replicate p=10 times random sampling n=1000 from a vector containing your
ordinal categories (1,2,3,4)
R <- replicate(10, sample(as.vector(seq(4)), 1000, replace = T))
Cheers,
Charles
On Fri, Apr 4, 2014 at 7:10 AM, thanoon younis
wrote:
> dear sir
> i want to si
dear sir
i want to simulate multivariate ordinal data matrix with categories (1,4)
and n=1000 and p=10.
thanks alot
thanoon
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
P
So can the same student be associated with multiple instructors? only
within the same school? or more general? by repeated student ID's do
you mean that a student in school A and a student in school B can both
have ID 1, but they are different students? or do you mean that
instructor #1 and Instr
Hi,
I want to simulate a data set with following condition:
There are 6 states with 12 schools. Each two schools are coming from one
states. For example school one and two from state A, school 3 and 4 from state
B and etc.
Each school has 10 unique instructors with random number of students mea
Hi everyone,
I am interested in doing a study to compare three analyzing methods namely,
ANOVA, GEE and multilevel approach for *categorical repeated measures data
using a simulation study in R*.
I am not an expert in R but I know some preliminaries in R. Therefore I am
desperately looking for some
On 04/08/2013 09:30, Rui Barradas wrote:
Hello,
See the help page for ?sample.
X <- sample(0:1, 1, replace = TRUE, prob = c(0.25, 0.75))
Hope this helps,
?rbinom would have been a better answer since simpler, faster,
algorithms are available in that case.
Or even
as.integer(runif(100
Thank you very much guys
On Sun, Aug 4, 2013 at 3:51 PM, Prof Brian Ripley wrote:
> On 04/08/2013 09:30, Rui Barradas wrote:
>
>> Hello,
>>
>> See the help page for ?sample.
>>
>> X <- sample(0:1, 1, replace = TRUE, prob = c(0.25, 0.75))
>>
>> Hope this helps,
>>
>
> ?rbinom would have been
So you looked at some unspecified help pages online and tried some unspecified
stuff? Try being more specific next time you post. For example, try reading the
footer of any R-help email. Note that it says read the Posting Guide, and
provide a reproducible example (at least of what you tried that
Hello,
See the help page for ?sample.
X <- sample(0:1, 1, replace = TRUE, prob = c(0.25, 0.75))
Hope this helps,
Rui Barradas
Em 04-08-2013 08:51, Preetam Pal escreveu:
Hi All,
I want to simulate a random variable X which takes values 1 and 0 with
probabilities 75% and 25% respectively
Hi All,
I want to simulate a random variable X which takes values 1 and 0 with
probabilities 75% and 25% respectively and then repeat the procedure 1
times.
I am sure this is trivial, I tried to look at the help pages online, but I
can't quite find it.
Appreciate your help.
Thanks and Reg
I am not aware of any such command so, I think, you may have to write one
yourself:
invert the CDF and use uniform random variable (runif) to sample
Mikhail
On Tuesday, June 11, 2013 16:18:59 cassie jones wrote:
> Hello R-users,
>
> I am trying to simulate from truncated skew normal distributi
Hello R-users,
I am trying to simulate from truncated skew normal distribution. I know
there are ways to simulate from skewed normal distribution such as rsn(sn)
or rsnorm(VGAM), but I could not find any command to simulate from a
truncated skew-normal distribution. Does anyone know how to do that
Tobias,
I'm not sure if this is what you're after, but perhaps it will help.
# create a list of 5 vectors
n <- 5
subsets <- lapply(1:n, function(x) rnorm(5, mean=80, sd=1))
# create another list that takes 2 bootstrap samples from each of the 5
vectors and puts them in a matrix
nbootstrap <- 2
t
Dear R experts,
I am trying to simulate a list containing data matrices. Unfortunately, I don't
manage to get it to work.
A small example:
n=5
nbootstrap=2
subsets<-list()
for (i in 1:n){
subsets[[i]] <- rnorm(5, mean=80, sd=1)
for (j in 1:nbootstrap){
test<-list()
Look at the harvestr package for one way to control multiple parallel
simulations and make sure that they have different seeds.
On Wed, Feb 20, 2013 at 4:24 PM, C W wrote:
> Thanks, Greg. I think you are right. I did simulation one right after
> the other, less than 2 seconds.
>
> But still,
On 20/02/2013 23:13, Greg Snow wrote:
To know for sure we need to know how you are running these different R
sessions, but here are some possibilities:
The help page for "set.seed" says that if no seed exists then the seed is
set based on the current time (and since 2.14.0 the process ID). So o
Thanks, Greg. I think you are right. I did simulation one right after the
other, less than 2 seconds.
But still, it was shocking to see identical samples, which I had to throw
away.
As a rule of thumb, should I do simulation in one R console, rather than
splitting the work into 2 consoles. I j
To know for sure we need to know how you are running these different R
sessions, but here are some possibilities:
The help page for "set.seed" says that if no seed exists then the seed is
set based on the current time (and since 2.14.0 the process ID). So one
possibility is that 2 of the sessions
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of C W
> Sent: Tuesday, February 19, 2013 5:32 PM
> To: r-help
> Subject: [R] Why R simulation gives same random results?
>
> Hi, list
> I am doing 100
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 HTM
On 03-01-2013, at 17:40, Simone Gogna wrote:
> Dear R users,
> suppose we have a random walk such as:
>
> v_t+1 = v_t + e_t+1
>
> where e_t is a normal IID noise pocess with mean = m and standard deviation =
> sd and v_t is the fundamental value of a stock.
>
> Now suppose I want a trading s
On 03-01-2013, at 17:40, Simone Gogna wrote:
> Dear R users,
> suppose we have a random walk such as:
>
> v_t+1 = v_t + e_t+1
>
> where e_t is a normal IID noise pocess with mean = m and standard deviation =
> sd and v_t is the fundamental value of a stock.
>
> Now suppose I want a trading s
Dear R users,
suppose we have a random walk such as:
v_t+1 = v_t + e_t+1
where e_t is a normal IID noise pocess with mean = m and standard deviation =
sd and v_t is the fundamental value of a stock.
Now suppose I want a trading strategy to be:
x_t+1 = c(v_t â p_t)
where c is a costant.
I kn
look at functions replicate and mvrnorm functions (the later in the MASS
package).
On Sat, Dec 1, 2012 at 12:02 PM, mboricgs wrote:
> Hello!
>
> How can I do 100 simulations of length 17 from bivariate bivariate normal
> distribution, if I know all 5 parameters?
>
>
>
> --
> View this message
Hello!
How can I do 100 simulations of length 17 from bivariate bivariate normal
distribution, if I know all 5 parameters?
--
View this message in context:
http://r.789695.n4.nabble.com/Simulation-in-R-tp4651578.html
Sent from the R help mailing list archive at Nabble.com.
__
On 13.11.2012 15:45, Christopher Desjardins wrote:
Hi,
I am running the following code based on the cpm vignette's code. I believe
the code is syntactically correct but it just seems to hang R. I can get
this to run if I set the sims to 100 but with 2000 it just hangs. Any ideas
why?
No: Work
Hi,
I am running the following code based on the cpm vignette's code. I believe
the code is syntactically correct but it just seems to hang R. I can get
this to run if I set the sims to 100 but with 2000 it just hangs. Any ideas
why?
Thanks,
Chris
library(cpm)
cpmTypes <- c("Kolmogorov-Smirnov","M
Hi,
I am looking for the best way or best package available for simulating a
genetic association between a specific SNP and a quantitative
phenotype. All of the packages I saw in R seem to be specialised in
pedigree data or in population data where coalescence and other
evolutionary factors are sp
Hi, I run this code to get the power of the test for modified bartlett's
test..but I'm not really sure that my coding is right..
#normal distribution unequal variance
asim<-5000
pv<-rep(NA,asim)
for(i in 1:asim)
{print(i)
set.seed(i)
n1<-20
n2<-20
n3<-20
mu<-0
sd1<-sqrt(25)
sd2<-sqrt(50)
sd3<-sqrt
Hi, I run this code to get the power of the test for modified bartlett's
test..but I'm not really sure that my coding is right..
#normal distribution unequal variance
asim<-5000
pv<-rep(NA,asim)
for(i in 1:asim)
{print(i)
set.seed(i)
n1<-20
n2<-20
n3<-20
mu<-0
sd1<-sqrt(25)
sd2<-sqrt(50)
sd3<-sqrt
On Mon, May 28, 2012 at 12:14 PM, Özgür Asar wrote:
> Dear Dila,
>
> Try the following:
>
> library(Rcmdr)
Or avoid the unncessary overhead of Rcmdr and use
library(car)
to provide levenTest instead.
> asim <- 1000
> pv<-NULL
It's also many orders of magnitude more efficient to preallocate "
Dear Dila,
Try the following:
library(Rcmdr)
asim <- 1000
pv<-NULL
for(i in 1:asim)
{
print(i)
set.seed(i)
g1 <- rnorm(20,0,2)
g2 <- rnorm(20,0,2)
g3 <- rnorm(20,0,2)
x <- c(g1,g2,g3)
group<-as.factor(c(rep(1,20),rep(2,20),rep(3,20)))
pv<-c(pv,leveneTest(x,group)$"Pr(>F)"[1])
}
Best
Ozgur
hello,
I try to run simulation of levene's test to find the p-value but the error
of replacement has length zero occur, could anyone help me to fix this
problem?
asim <- 1000
pv<-rep(NA,asim)
for(i in 1:asim)
{print(i)
set.seed(i)
g1 <- rnorm(20,0,2)
g2 <- rnorm(20,0,2)
g3 <- rnorm(20,0,2)
x
On Apr 5, 2012, at 10:57 PM, Christopher Kelvin wrote:
Hello,
i need to simulate 100 times, n=40 ,
the distribution has 90% from X~N(0,1) + 10% from X~N(20,10)
Is my loop below correct?
Thank you
n=40
for(i in 1:100){
x<-rnorm(40,0,1) # 90% of n
You are overwriting x and y and at the end o
Hello,
i need to simulate 100 times, n=40 ,
the distribution has 90% from X~N(0,1) + 10% from X~N(20,10)
Is my loop below correct?
Thank you
n=40
for(i in 1:100){
x<-rnorm(40,0,1) # 90% of n
z<-rnorm(40,20,10) # 10% of n
}
x+z
__
R-help@r-project.o
The follwing is a code snippet from a power simulation
program that I'm using:
estbeta<-fixef(fitmodel)
sdebeta<-sqrt(diag(vcov(fitmodel)))
for(l in 1:betasize)
{
cibeta<-estbeta[l]-sgnbeta[l]*z1score*sdebeta[l]
if(beta[l]*cibeta>0) powaprox[[l]]<-powaprox[[l]]+1
Suggestions? -- Yes.
1) Wrong list.. Post on R-sig-mixed-models, not here.
2) Follow the posting guide and provide the modelformula, which may
well be the source of the difficulties (overfitting).
-- Bert
On Fri, Dec 16, 2011 at 1:56 PM, Scott Raynaud wrote:
> I'm using an R program (which I d
I'm using an R program (which I did not write) to simulate multilevel data
(subjects in locations) used in power calculations. It uses lmer to fit a
mixed logistic model to the simulated data based on inputs of means,
variances, slopes and proportions:
(fitmodel <- lmer(modelformula,data,famil
Perhaps you might want to abstract your code a bit and try something like:
X = rnorm(500) # Some Data
replicate(1e4, mean(sample(X, 500, replace = T)))
Obviously you can set up a loop over your data sets as needed.
Michael
On Sat, Nov 12, 2011 at 6:46 PM, Francesca wrote:
> Dear Contributors,
Dear Contributors,
I am trying to perform a simulation over sample data,
but I need to reproduce the same simulation over 4 groups of data. My
ability with for loop is null, in particular related
to dimensions as I always get, no matter what I try,
"number of items to replace is not a multiple
Why don't you use sample;
> sample(1:10,10,replace=TRUE)
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
On Behalf Of BSanders
Sent: 26 October 2011 08:49
To: r-help@r-project.org
Subject: Re: [R] Simulation from discrete uniform
If yo
If you wanted a discrete uniform from 1-10 use: ceiling(10*runif(1))
if you wanted from 0-12, use: ceiling(13*runif(1))-1
--
View this message in context:
http://r.789695.n4.nabble.com/Simulation-from-discrete-uniform-tp3434980p3939694.html
Sent from the R help mailing list archive at Nabble.com.
On Jul 21, 2011, at 1:42 PM, Benjamin Caldwell wrote:
That is, run all possible combinations of the two vectors through the
equation.
*Ben *
For "all combinations" the usual route is data preparation with either
expand.grid() or outer()
On Thu, Jul 21, 2011 at 10:04 AM, Benjamin Caldwel
That is, run all possible combinations of the two vectors through the
equation.
*Ben *
On Thu, Jul 21, 2011 at 10:04 AM, Benjamin Caldwell wrote:
> Hi,
> I'm trying to run a basic simulation and sensitivity test by running an
> equation with two variables and then plotting the results against
Hi,
I'm trying to run a basic simulation and sensitivity test by running an
equation with two variables and then plotting the results against each of
the vectors. R is running the vectors like this : 0 with 0, 1 with 1, etc. I
would like it to run them like 0 for 1:100, 1 for 1:100, and then the
re
On Mon, Jun 06, 2011 at 04:50:57PM +1000, Stat Consult wrote:
> Dear ALL
> I want to simulate data from Multivariate normal distribution.
> GE.N<-mvrnorm(25,mu,S)
> S <-matrix(rep(0,1),nrow=100)
> for( i in 1:100){sigma<-runif(100,0.1,10);S
> [i,i]=sigma[i];mu<-runif(100,0,10)}
> for (i in 1:20
Dear ALL
I want to simulate data from Multivariate normal distribution.
GE.N<-mvrnorm(25,mu,S)
S <-matrix(rep(0,1),nrow=100)
for( i in 1:100){sigma<-runif(100,0.1,10);S
[i,i]=sigma[i];mu<-runif(100,0,10)}
for (i in 1:20){for (j in 1:20){if (i != j){S [i,j]=0.3*sigma[i]*sigma[j]}}}
for (i in 21:
Dear ALL
I want to simulate data from Multivariate normal distribution.
GE.N<-mvrnorm(25,mu,S)
S <-matrix(rep(0,1),nrow=100)
for( i in 1:100){sigma<-runif(100,0.1,10);S
[i,i]=sigma[i];mu<-runif(100,0,10)}
for (i in 1:20){for (j in 1:20){if (i != j){S [i,j]=0.3*sigma[i]*sigma[j]}}}
for (i
Hi Serdar,
Take a look at the following:
> sample(0:9, 100, replace = FALSE)
Error in sample(0:9, 100, replace = FALSE) :
cannot take a sample larger than the population when 'replace = FALSE'
> sample(0:9, 100, replace = TRUE)
[1] 5 6 5 7 3 0 8 4 8 2 2 4 7 6 0 7 0 0 0 7 5 6 3 6 0 9 6 1 2 6 9
Hi
Also , same problem to create discrete uniform Distribution ,
But sample () and runif() not useful to generate discrete uniform .
Ex:
> u<-round(runif(10*10,min=1,max=10),0)
> table(u)
u
1 2 3 4 5 6 7 8 9 10
6 10 9 10 14 6 11 14 12 8
Not useful for large number
OR
--Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of cassie jones
> Sent: Monday, May 16, 2011 5:28 PM
> To: r-help@r-project.org
> Subject: [R] simulation from truncated poisson
>
> Dear all,
>
> I need to simul
uniform between that value and 1, then feed that
> uniform into the qpois function.
>
>
>
> *From:* cassie jones [mailto:cassiejone...@gmail.com]
> *Sent:* Monday, May 16, 2011 7:46 PM
> *To:* Greg Snow
> *Cc:* r-help@r-project.org
> *Subject:* Re: [R] simulation from tr
l.com]
Sent: Monday, May 16, 2011 7:46 PM
To: Greg Snow
Cc: r-help@r-project.org
Subject: Re: [R] simulation from truncated poisson
It is truncated from left.
On Mon, May 16, 2011 at 6:33 PM, Greg Snow
mailto:greg.s...@imail.org>> wrote:
Which direction is it truncated? (only values
: Monday, May 16, 2011 5:28 PM
To: r-help@r-project.org
Subject: [R] simulation from truncated poisson
Dear all,
I need to simulate values from a Poisson distribution which is truncated at
certain value 'a'. Can anyone tell me if there is in-built package in R
which can simulate from a
Dear all,
I need to simulate values from a Poisson distribution which is truncated at
certain value 'a'. Can anyone tell me if there is in-built package in R
which can simulate from a truncated Poisson? If not, what should be the
steps to write a function which would do that?
Thanks in advance.
Hi Shane,
it sounds to me as though you have a fairly well-defined problem. You
want to generate random numbers with a specific mean, variance, and
correlation with another random varaible. I would reverse-enginerr
the fuinctions for simple linear regression to get a result like
y = beta_0 + be
I have the following script for generating a dataset. It works like a champ
except for a couple of things.
1. I need the variables "itbs" and "map" to be negatively correlated with the
binomial variable "lunch" (around -0.21 and -0.24, respectively). The binomial
variable "lunch" needs to
?sample
-Oprindelig meddelelse-
Fra: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] På
vegne af cassie jones
Sendt: 8. april 2011 03:16
Til: r-help@r-project.org
Emne: [R] Simulation from discrete uniform
Dear all,
I am trying to simulate from discrete uniform
Hi:
Suppose X has a discrete uniform distribution on the sample space S = {0, 1,
2, ..., 9}. Then a random sample of size 100 from this distribution, for
example, would be
dus <- sample(0:9, 100, replace = TRUE)
# Checks:
table(dus)
lattice::barchart( ~ table(dus), xlim = c(0, 20))
The sample sp
Dear all,
I am trying to simulate from discrete uniform distribution. But I could not
find any in-built code in R. Could anyone help me please?
Thanks in advance for the time and help.
Cassie
[[alternative HTML version deleted]]
__
R-help
> Date: Mon, 28 Feb 2011 19:18:18 -0800
> From: kadodamb...@hotmail.com
> To: r-help@r-project.org
> Subject: [R] Simulation
>
> I tried looking for help but I couldn't locate the exact solution.
> I have data that has sever
Well, knowing how your data looks like would definitely help!
Say your data object is called "mydata", just paste the output from
dput(mydata) into the email you want to send to the list.
Ivan
Le 3/1/2011 04:18, bwaxxlo a écrit :
I tried looking for help but I couldn't locate the exact solutio
I tried looking for help but I couldn't locate the exact solution.
I have data that has several variables. I want to do several sample
simulations using only two of the variables (eg: say you have data between
people and properties owned. You only want to check how many in the samples
will come up
Dear Kjetil,
Thank you so much for your advice on my question.
Best Regards,
Wonsang
2011/2/10 Kjetil Halvorsen
> What you can do to find out is to type into your R session
> RSiteSearch("multivariate fractional gaussian")
>
> That seems to give some usefull results.
>
> Kjetil
>
> On Tue, F
What you can do to find out is to type into your R session
RSiteSearch("multivariate fractional gaussian")
That seems to give some usefull results.
Kjetil
On Tue, Feb 8, 2011 at 1:51 PM, Wonsang You wrote:
>
> Dear R Helpers,
>
> I have searched for any R package or code for simulating multivar
Dear R Helpers,
I have searched for any R package or code for simulating multivariate
fractional Brownian motion (mFBM) or multivariate fractional Gaussian noise
(mFGN) when a covariance matrix are given. Unfortunately, I could not find
such a package or code.
Can you suggest any solution for mul
On 05/01/2011 17:40, Bert Gunter wrote:
My hypothesis was specified before I did my experiment. Whilst far from
perfect, I've tried to do the best I can to assess rise in resistance,
without going into genetics as it's not possible. (Although may be at the
next institution I've applied for MSc).
On 05/01/2011 16:37, Mike Marchywka wrote:
Date: Wed, 5 Jan 2011 15:48:46 +
From: benjamin.w...@bathspa.org
To: r-help@r-project.org
Subject: [R] Simulation - Natrual Selection
Hi,
I've been modelling some data over the past few days, of my work,
repeatedly challenging microbes
> Date: Wed, 5 Jan 2011 15:48:46 +
> From: benjamin.w...@bathspa.org
> To: r-help@r-project.org
> Subject: [R] Simulation - Natrual Selection
>
> Hi,
>
> I've been modelling some data over the past few days, of my work,
> repeatedly challenging microb
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