similar to: time series simulation

Displaying 20 results from an estimated 5000 matches similar to: "time series simulation"

2006 Sep 18
1
multiple density function
Hi everybody I'm new in R so the question will be easy for you I'm running multiple density functions taking account of the following conditions: mean=seq(10,1,length=10) var=seq(3,1,length=10) How can I describe the density functions on the same chart? thanks Marcella -- View this message in context: http://www.nabble.com/multiple-density-function-tf2289386.html#a6358504 Sent
2004 Jul 24
3
Population simulation.
Hello, can anyone tell me if R has any special function for simulating the structure of human populations? Something like the genetic algorithm? I need to simulate a sample of a population with a specific structure. Is there something on R that can help me? Thanks to everyone. __________________________________________________________
2009 May 29
1
Mean of lognormal in base-2
Hi, Does anyone know what the mean value of a lognormal distribution in base-2 is? I am simulating stochastic population growth and if I were working in base-e, I would do:lambda <- 1.1 #multiplicative growth rates <- 0.6 #stochasticity (std. dev)lognormal <- rlnorm(100000, log(lambda) - (s^2)/2, s)## or lognormal <- exp( rnorm( 100000, log(lambda) - (s^2)/2,
2008 Aug 21
3
[help] simulation of a simple Marcov Stochastic process for population genetics
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,
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.
2009 Feb 12
1
Using nls or nls.lm with a simulation output
We would like to fit parameters using a simulation with stochastic processes as theoretical values. We generate a simple exemple with nls.lm to see the logic and the problem: First without stochasticity (it is a dummy example, the fited value is simple the mean of a set of 10 numbers): #Ten numbers x <- 1:10 #Generate 10 Gaussian random number with mean=3 sd=1 simy <- rnorm(length(x),
2006 Sep 14
5
Beta stochastic simulation
Hi, I am finding that I get quite different results when I interchange the following "equivalent" lines for sampling from a beta distribution in my r script. The rbeta line is correct judging by the summary statistics of the simulated values, while the qbeta line consistently leads to a higher mean simulated value. simulation <- rbeta(1, alpha, beta) simulation <- qbeta(runif(1),
2016 Apr 20
2
simulation in R
Hi R user, Would you mind to help me to find the range with stochastic events? For example, daT<-structure(list(sn = 1:14, growthrate = c(0.5, 0.6, 0.7, 0.99, 0.1, 0.3, 0.4, 0.5, 0.5, 0.2, 0.1, 0.4, 0.3, 0.43)), .Names = c("sn", "growthrate"), class = "data.frame", row.names = c(NA, -14L)) I want to find the ranges of growth rate of the above data using Mote
2003 Feb 11
1
Dynamic Linear Models for Times Series - Implemented?
Hi, I was wondering whether a package that can perform dynamic linear models on times series data was available for R? Many Thanks, Gavin Simpson %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Gavin Simpson [T] +44 (0)20 7679 5522 ENSIS Research Fellow [F] +44 (0)20 7679 7565 ENSIS Ltd. & ECRC [E] gavin.simpson at
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
2005 Nov 13
1
correlating irregular time series
I have some time stamped events that are supposed to be unrelated. I have plotted them and that assumption does not appear to be valid. http://metrak.com/tmp/sevents.png is a plot showing three sets of events over time. For the purpose of this exercise, the Y value is irrelevant. The series are not sampled at the same time and are not equispaced (just events in a log file). The plot is
2016 Apr 20
0
simulation in R
I realized that there was a typo error. I mean "Monte Carlo Simulation" ________________________________________ From: R-help <r-help-bounces at r-project.org> on behalf of Kristi Glover <kristi.glover at hotmail.com> Sent: April 19, 2016 11:48 PM To: R-help Subject: [R] simulation in R Hi R user, Would you mind to help me to find the range with stochastic events? For
2009 Jan 26
1
generic questions about probability and simulation -- not directly related to R
Dear helpers, As the title says, my question is not directly related to R. I find, however, that there are many people who are both knowledgeable and kind in this email list, and so decided to give it a try. I do stochastic simulations. Parameter values used in simulation often come from the observations of the real word phenomena. Parameter values are often given as "rates" (of
2008 Jun 18
1
Complex Time Series
Hi R masters, In my work I analyse a time serie of number of birth in State of Rio de Janeiro. After study de ACF e p ACF I conclude the model is: Non seasonal ar(1) In 7 days lag 7 days seasonal ma(1) In 364 days lag 364 days seasonal ma(1) If the time serie was Non seasonal ar(1) with one seasonal ma(1) is simple using command arima for fit a time serie, but I don't know HOW TO fit a
2011 Jul 02
1
Simulating inhomogeneous Poisson process without loop
Dear all I want to simulate a stochastic jump variance process where N is Bernoulli with intensity lambda0 + lambda1*Vt. lambda0 is constant and lambda1 can be interpreted as a regression coefficient on the current variance level Vt. J is a scaling factor How can I rewrite this avoiding the loop structure which is very time-consuming for long simulations? for (i in 1:N){ ... N <- rbinom(n=1,
2011 Dec 16
1
Fortune? -- was Re: optim with simulated annealing SANN ...
Folks: I thought John Nash's comment below was profound and a possible Fortunes candidate: (Aside: I believe it applies to a great deal of what is discussed on this list, not just stochastic optimization.) Cheers, Bert ... (in the context of stochastic optimization) >... As with many tools in this domain, for effective use they > require more knowledge than many of their users
2007 Jul 16
1
question about ar1 time series
Hello everybody, I recently wrote a "program" that to generate AR1 time series, here the code: #By Jomopo. Junio-2007, Leioa, Vizcaya #This program to create the AR1 syntetic series (one by one) #Where the mean is zero, but the variance of the serie AR1 and #the coef. of AR1 are be changed. If var serie AR1 = 1 then is standarized! #Final version for AR1 time series program #Mon Jul
2005 Jan 13
1
Re:Time-Series
Hi, you can address to a single ts in a multivariate ts object by namets[,index]. See this example: > dati X Y 1 100 200 2 150 210 3 180 220 4 200 230 5 220 250 > serie<-ts(dati,start=1999) > serie Time Series: Start = 1999 End = 2003 Frequency = 1 X Y 1999 100 200 2000 150 210 2001 180 220 2002 200 230 2003 220 250 > serie[,1] ## first ts Time Series: Start =
2009 Oct 15
4
Generating a stochastic matrix with a specified second dominant eigenvalue
Hi, Given a positive integer N, and a real number \lambda such that 0 < \lambda < 1, I would like to generate an N by N stochastic matrix (a matrix with all the rows summing to 1), such that it has the second largest eigenvalue equal to \lambda (Note: the dominant eigenvalue of a stochastic matrix is 1). I don't care what the other eigenvalues are. The second eigenvalue is
2009 Apr 02
1
Time series analysis with irregular time-series
Dear R users I am currently investigating time series analysis using an irregular time series. Our study is looking at vegetation change in areas of alien vegetation growth after clearing events. The irregular time series is sourced from Landsat ETM+ data, over a six year period I have 38 scenes. For certain periods I have monthly data while for others, images are up to three months apart. So far