similar to: stochastic models for population growth

Hello, It's not easy to express clearly what I have in mind by stochastic growth models. I've been working with a couple of titles -Stochastic Models in Biology, for one, but both date back a decade or more. I'll try to illustrate the model a little more. A reasonably comparable situation is Bolker's analysis of how many flowers are created on a given plant among a patch of

Dear all, I am running matrix population models using package "popbio". In a deterministic model {i.e., transition matrix is defined as A <- matrix(c(0.70, 0.70,0.35,0.50), nrow=2,byrow=TRUE}, population growth rate can be estimated from the dominant eigenvalue {command "eigen.analysis"}. However, I cannot figure out the way to compute the asymptotic stochastic population

--- On Mon, 3/12/12, aleksandr shfets <a_shfets at mail.ru> wrote: > From: aleksandr shfets <a_shfets at mail.ru> > Subject: Fwd: Re[2]: [R] B-spline/smooth.basis derivative matrices > To: "Vassily Shvets" <shv736 at yahoo.com> > Received: Monday, March 12, 2012, 5:15 PM > > > > -------- ???????????? ????????? > -------- > ?? ????:

Hello, I'm used to working with R in estimation of distributions and statistical models. I'd like to estimate a simple model of an output y(t) based on a concentration as independent variable, using a timed series of experimental data; I've seen this I think somewhere in R? I'd appreciate to hear if anybody has used this with success. regards, S

Hello, I've noticed that SPLUS seems to have a function for evaluating derivative matrices of splines. I've found the R function that evaluates matrices from 'smooth.spline'; maybe someone has written something to do the same with smooth.basis? regards, s

Hello, I am new to R and I am having problems trying to model logistic population growth with the deSolve package. I would like to run the model for four populations with the same initial population and carrying capacity but with different growth rates and put the results into a data frame. When I run the following lines of code I get unexpected results from "output" but the format is

Hi, this is my first time using R. I want to simulate the following process: "in a population of size N, there are i individuals bearing genotype A, the number of those bearing A is j in the next generation, which following a binominal distribution (choose j from 2*N, the p is i/2*N), to plot the probability of the next generations, my script is as follows. It cannot run successfully,

Hello, I've noticed that SPLUS has a function for evaluating the derivative matrices of splines. I've also noticed that there's a function in R for evaluating matrices from smooth.spline; maybe someone knows if something has been written to evaluate matrices from 'smooth.basis'? regards, s

Dear all, I want to program my own models about Stochastic Frontier Analysis and Linear programming (Data Envelopment Analysis). In this context, is there anyone that may help me with some simple tutorials and scripts about these issues? Thanks a lot. -- Marcus Vinicius Pereira de Souza, Prof. [[alternative HTML version deleted]]

Do anyone now R packages that run/test stochastic dominance with respect to a function (SDRF) and/or stochastic efficiency with respect to a function (SERF)? Peter Maclean Department of Economics UDSM [[alternative HTML version deleted]]

Dear all, I want to finished my paper by latent class Stochastic Frontier Analysis , but i can not find the package, is there anyone that may help me Thanks a lot. [[alternative HTML version deleted]]

I need to estimate maximum tree crown radius and am looking for a package to prepare stochastic frontier models in R. I have not found any package references on Nabble R help, google, or R help. Any tips on a package for this? With regards, Aaron Trowbridge Researcher BV Research Centre Smithers B.C. -- View this message in context:

Dear everyone, i`m a german economics student, writing my master´s thesis about "Multivariate Volatility Models". After having read about theoretical aspects of Multivariate GARCH ans Stochastic Volatility Models, I would like to compare DCC-GARCH and DC-SV with help of an empirical application. I figuered out that one has to use MCMC-simulation-methods for that. Some days ago I

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.

Hi all, Could anybody point me to some overview/survey papers about using particle filters and sequential monte carlo methods to estimate stochastic volatilities? I couldn't find any such articles giving a big-picture view of the literature. How do these estimation methods compare to EMM and other Bayesian methods for estimating stochastic volatilities? Also, I am looking for some

Computational Aspects of Simulation and Inference for Stochastic Processes and the YUIMA Project This two-day workshop is aimed at presenting the latest results on simulation and inference for stochastic processes and their current and prospect implementation within the YUIMA R package. Dates: March 27 (Tue) 9:15-12:15, 14:45-17:45 March 28 (Wed) 9:15-12:15, 14:45-17:45 Location:

Hi, I need some help with solving functional equations (Bellman's or Euler's) with numerical methods. I have read the relevant books (Kenneth L Judd: Numerical methods in economics, and some others), but have no practical experience. All the examples in these books are in Matlab, but I would prefer R, since I have been using that for some time and I think that it is generally much nicer

Dear colleagues, I?m a new R-help user. I?ve read the advertisements about the good manners and I hope to propose a good question. I?m using R to build an epidemiological SEIR model based on ODEs. The odesolve package is very useful to solve deterministic ODE systems but I?d like to perform a stochastic simulation based on Markov chain Montecarlo methods. I don?t know which packages could be

Hi all, Does anybody have the source code of stochastic volatility models in R or Matlab, for example, the Bayesian based or the simulation based SV estimations as described by Prof Eric Zivot in the following discussion? https://stat.ethz.ch/pipermail/r-sig-finance/2005q4/000501.html -------------- I am wondering what is the current status of estimating stochastic vol models and what's

Hi! A few weeks ago, I have uploaded a new R package "frontier" for Stochastic Frontier Analysis (SFA) [1] to CRAN [2]. It includes the FORTRAN code of Tim Coelli's [3] software "Frontier 4.1" [4]. Hence, the R package "frontier" should have the same capabilities as "Frontier 4.1", i.e. Maximum Likelihood Estimation of Stochastic Frontier Production