This would almost certainly fit better on the r-sig-mixed-models
list,rather than here. You are more likely to get authoritative responses
about this specialized statistical topic there.
Also -- these are **plain text** mailing lists. Please do not post in html.
Cheers,
Bert
Bert Gunter
"The t
Hello,
I would like to simulate nested data, where my mixed effects model fitted
to real data has the form:
y ~ time + (1 | site/subject)
I then take the hyper-parameters from this model to simulate fake data,
using this function:
create_fake <- function(J,K,L,HP,t){
d
Sent: Monday, June 29, 2015 9:21 AM
To: PIKAL Petr
Cc: r-help
Subject: Re: [R] Simulating data
ok. ill just paste the data here ... hope it helps
y
x
5721
20175
4285
1
4327
59426
4964
75536
7899
79432
11140
125735
11843
89411
18146
124805
24712
110859
31993
178038
t; > Sent: Monday, June 29, 2015 8:36 AM
> > To: r-help
> > Subject: [R] Simulating data
> >
> > i wish to simulate data to generate twice the sample size for testing a
> > model.
> >
> > the two fields to be simulated are y and x, in the attached file.
Hi
Attachments are usually discarded.
maybe ?sample
Petr
> -Original Message-
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of deva d
> Sent: Monday, June 29, 2015 8:36 AM
> To: r-help
> Subject: [R] Simulating data
>
> i wish to simulate data
i wish to simulate data to generate twice the sample size for testing a
model.
the two fields to be simulated are y and x, in the attached file.
as you will see, these represent data of several companies, of different
sizes, for a 11 year period. the distribution is not really fitting into
any kn
The examples on the help page for the function "simfun" in the
TeachingDemos package have some examples of simulating data from
nested designs with some terms fixed and some random. I don't think
any of the examples match your conditions exactly, but could be
modified to do so (changing a random e
Hi,
I am trying to 'create' a nested design with A, B nested in A and C nested
in B. C is random and the others are fixed.
Does anyone have any idea how to do this?
I would also like to try the other nested designs with all random and all
effects fixed.
--
Thanks,
Jim.
[[alternative HTM
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If you have received this e-mail in error please contact the sender.
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Mª Teresa Martinez Soriano
> Sent: 4. april 2014 10:49
> To: r-help@r-proj
Hi to everyone
To simulate data I only know this command:
rnorm(n , mean, sd)
It exists another way to specify Median and range as well?
The point is that I have this information about the variable:
Median: 4.3
Mean: 4.2
SD: 1.8
Range: 0-8
and I need a boxplot, but I don't have the origin
Hi,
I am wanting to simulate data where a percentage of the data has
multiple duplicated id variables (with unique values of another factor
variable for the dupicated id variables). Im having trouble figuring
out an efficent way to do so.
For example, consider this mock output [Note: Although the
Hi,
I wrote a script in order to simulate data, which I will use for evaluating
missing data and imputation. However, I'm having trouble with the last part
of my script, in which a dataframe is constructed without missing values.
This is my script:
y1 <- rnorm(10,0,3)
y2 <- rnorm(10,3,3)
y3 <-
Hi Sarah,
There is one thing you need to think about: how do you choose which
values should not be removed if you have more than 20 and which should
be if you have less than 20. In my code, I've just done it with
sample(), which might not be what you need.
Here is what I have:
if (length(whi
Hello,
I would like to run a script in which a loop is included. Since I'm new to
R, I cannot manage the following problem. I really hope someone could help
me out.
Data in the variable Y should be removed from the simulated data set with
probability 0.50 if the variable X has a value below zero
Dirty hack, but it's working.
library(MASS)
mu <- aic.mv$best.mo...@expected.value
sigma <- aic.mv$best.mo...@variance
mvrnorm(100,mu,sigma)
If you'd like to follow the rules, look for the functions to extract
the expected value and the variance of the best model out of the
stepAIC.ghyp object.
Sir,
I am working on fitting distribution on multivariate financial data and then
simulate observations from that fitted distribution. I use stepAIC.ghyp()
function of 'ghyp' library which select the best fitted distribution from
generalized hyperbolic distribution class on the given dataset.
data
Hello
Your attachement didn't seem to get through.
You can simulate data using rnorm() or any of the r*() functions [1].
You can also use it to add noise to a custom function that you use to
generate your specific data.
Liviu
[1] http://www.statmethods.net/management/functions.html
On 8/25/09,
Dear All
I know that you do not have to help me but please do, i am new to R as a CPI
compiler, i just need to do a sample to see which sampling method best works in
different situations, therefore since this is for practice purposes nobody will
finance a real project thats why i need you to h
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