Displaying 20 results from an estimated 100 matches similar to: "Discrete trait Ornstein–Uhlenbeck in R?"
2012 Jul 20
1
fitting Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD
Dear friends
i am trying to fit an Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD
method.
i found these formulas on
http://www.sitmo.com/article/calibrating-the-ornstein-uhlenbeck-model/
this is the mean-reverting process
http://r.789695.n4.nabble.com/file/n4637271/process.txt process.txt
and this is the script that i am using.......
ouFit.ML=function(spread) {
n=length(spread)
2007 Nov 28
1
simulating a 2-parameter integrated ornstein-uhlenbeck process?
hello everyone,
i'm trying to simulate a 2-parameter integrated ornstein-uhlenbeck (IOU) process, but i'm not sure exactly where to start (which package, which function). the motivation is the paper by taylor et. al. (JASA 1994) "a stochastic model for the analysis of longitudinal aids data." the model they suggest consists of a combination of fixed and random effects, a
2009 Mar 09
2
mean reverting model
dear useRs,
i'm working with a mean reverting model of the following specification:
y = mu + beta(x - mu) + errorterm, where mu is a constant
currently I estimate just y = x (with lm()) to get beta and then
calculate mu = estimated intercept / (1-beta).
but I'd like to estimate mu and beta together in one regression-step
and also get the test-statistics (including parameter
2019 Apr 05
0
new R packages for phylogenetic compartive methods
Dear all,
I wanted to let you know about four phylogenetic comparative methods (PCM) packages that have become available on (3 on CRAN and 1 on GitHub) recently that hopefully will be interesting to somebody. Three of them go significantly beyond the Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes.
1) There is a new version of mvSLOUCH available. The most important change is that
the
2019 Apr 05
0
new R packages for phylogenetic compartive methods
Dear all,
I wanted to let you know about four phylogenetic comparative methods (PCM) packages that have become available on (3 on CRAN and 1 on GitHub) recently that hopefully will be interesting to somebody. Three of them go significantly beyond the Brownian motion (BM) and Ornstein-Uhlenbeck (OU) processes.
1) There is a new version of mvSLOUCH available. The most important change is that
the
2007 May 31
0
adehabitat version 1.6
Dear all,
I have just uploaded to CRAN the version 1.6 of the
package 'adehabitat'. Significant changes are
listed below:
* The package has been reorganized into four parts (see
?adehabitat-package for a description): (i) management of raster maps,
(ii) habitat selection / ecological niche analysis, (iii) home range
analysis, and (iv) analysis of animals trajects. The package contains
2007 May 31
0
adehabitat version 1.6
Dear all,
I have just uploaded to CRAN the version 1.6 of the
package 'adehabitat'. Significant changes are
listed below:
* The package has been reorganized into four parts (see
?adehabitat-package for a description): (i) management of raster maps,
(ii) habitat selection / ecological niche analysis, (iii) home range
analysis, and (iv) analysis of animals trajects. The package contains
2006 Oct 27
1
Error using "White-corrected" Anova (white.adjust="hc3")
Hello.
I try to compute a "White-corrected" ANOVA. Therefore I use the command "Anova" implemented in the car()-package):
Anova(modelname, white.adjust="hc3")
and receive the error message:
"Fehler in SS[i] <- SS.term(names[i]) : nichts zu ersetzen" (German)
"Error in SS[i] <- SS.term(names[i]) : nothing to replace" (probably being the
2004 Mar 12
0
Latent trait models
Hi,
I am looking for any procedure in R to fit "Latent variables models" in particular "Latent trait models (i.e. for binary data)". could anyone help me?
Many thanks ,
Dr Abderrahim Oulhaj
Oxford University
Department of Pharmacology
Mansfield Road
Oxford OX1 3QT
Tel: +44 1865 224098
Fax: +44 1865 224099
Email: abderrahim.oulhaj@pharmacology.oxford.ac.uk
2013 Jun 11
0
Rao's quadratic entropy with fuzzy coded trait data
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2005 Mar 15
0
New package for latent trait models
Dear R-users,
I'd like to announce the release of my new package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch
model) under the Item Response Theory approach. The latent trait model
is the analogous of the factor analysis model for Bernoulli response
data. "ltm" fits the linear one- and two-factor models but also allows
for
2005 Mar 15
0
New package for latent trait models
Dear R-users,
I'd like to announce the release of my new package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch
model) under the Item Response Theory approach. The latent trait model
is the analogous of the factor analysis model for Bernoulli response
data. "ltm" fits the linear one- and two-factor models but also allows
for
2011 Sep 21
1
glmnet for Binary trait analysis
Hello,
I got an error message saying
Error in lognet(x, is.sparse, ix, jx, y, weights, offset, alpha, nobs, :
NA/NaN/Inf in foreign function call (arg 5)
when I try to analysis a binary trait using glmnet(R) by running the
following code
library(glmnet)
Xori <- read.table("c:\\SNP.txt", sep='\t');
Yori <- read.table("c:\\Trait.txt", sep=',');
2011 Nov 02
1
nproc parameter in efpFunctional
Hello all,
could anyone explain the exact meaning of parameter nproc? Why different
values of nproc give so different critical values, i.e.
meanL2BB$computeCritval(0.05,nproc=3)
[1] 0.9984853
meanL2BB$computeCritval(0.05,nproc=1)
[1] 0.4594827
The strucchange-package description gives "integer specifying for which
number of processes Brownian motions should be simulated" - do I need
2010 Nov 19
2
simple loop problemo (Geo brownian motion)
I would like to plot multiple random walks onto the same graph. My p
variable dictates how may random walks there will be.
par(mfrow=c(1,1))
p <- 100
N <- 1000
S0 <- 10
mu <- 0.03
sigma <- 0.2
nu <- mu-sigma^2/2
x <- matrix(rep(0,(N+1)*p),nrow=(N+1))
y <- matrix(rep(0,(N+1)*p),nrow=(N+1))
t<- (c(0:N))/N
for (j in 1:p)
{
z <- rnorm(N,0,1)
x[1,j] <- 0
y[1,j]
2009 Apr 03
2
Geometric Brownian Motion Process with Jumps
Hi,
I have been using maxLik to do some MLE of Geometric Brownian Motion Process and everything has been going fine, but know I have tried to do it with jumps. I have create a vector of jumps and then added this into my log-likelihood equation, know I am getting a message:
NA in the initial gradient
My codes is hear
#
n<-length(combinedlr)
j<-c(1,2,3,4,5,6,7,8,9,10)
2017 Jan 16
4
[RFC 0/2] Propose a new pointer trait.
Hi,
I'm part of an engineering team doing research on persistent memory support and
we have stumbled upon an interesting problem. The issue is, we would like to be
able to use the standard library containers in a persistent memory context
(think NVDIMM-N). What I mean is that you allocate a container from said
memory, use it like you normally would. After the application terminates,
expectedly
2011 Feb 08
1
Simulation of Multivariate Fractional Gaussian Noise and Fractional Brownian Motion
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 multivariate FBM and FGN simulation? Thank
you for your help.
Best Regards,
Ryan
-----
Wonsang You
2003 Apr 15
1
Simulation of Stochastic processes
Hi:
I was wondering whether I can find some help for computer simulation of
stochastic processes (e.g. Brownian motion), for
pedagogicl/instructional purposes. Any help would be appreciated.
thanks,
Ravi.
2008 Jun 13
1
R and Browninan Motion/ Langevin Equation package
Hi,
I'm writing a short course tutorial to Browninan Motion/ Langevin Equation.
At the end of the theory section I wanted to add a short GNU R example, so the students can play a little around.
I already looked in the MASS book (by Venables and Ripley) but I couldn't find any Brownian Motion/ Langevin Equation package.
Are there any good packages or tutorials available which cover R and