dY_t = (1.5(5-Y_t)+3sin(0.25 pi t ))dt+0.25sqrt(Y_t)dB_t
where dW_t and dB_t are standard Brownian motions, t is time and X_0 = 10, Y_0 = 5.
Usage
data("SDEsim4")
Format
A data frame with 401 observations on the following 3 variables.
Xt
Xt trajectory of the diffusion.
Yt
Yt trajectory of the diffusion.
time
Time vector.
Examples
data(SDEsim4)
attach(SDEsim4)
# Have a look at the time series:
plot(Xt~time,type='l',col='blue',ylim=c(0,25),main='Simulated Data',
xlab='Time (t)',ylab='State',axes=FALSE)
lines(Yt~time,col='red')
axis(1,seq(0,100,5))
axis(1,seq(0,100,5/10),tcl=-0.2,labels=NA)
axis(2,seq(0,25,2))
axis(2,seq(0,25,2/10),tcl=-0.2,labels=NA)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(DiffusionRgqd)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DiffusionRgqd/SDEsim4.Rd_%03d_medium.png", width=480, height=480)
> ### Name: SDEsim4
> ### Title: A Simulated Non-Linear Bivariate Diffusion With
> ### Time-Inhomogeneous Coefficients
> ### Aliases: SDEsim4
> ### Keywords: datasets
>
> ### ** Examples
>
> data(SDEsim4)
> attach(SDEsim4)
> # Have a look at the time series:
> plot(Xt~time,type='l',col='blue',ylim=c(0,25),main='Simulated Data',
+ xlab='Time (t)',ylab='State',axes=FALSE)
> lines(Yt~time,col='red')
> axis(1,seq(0,100,5))
> axis(1,seq(0,100,5/10),tcl=-0.2,labels=NA)
> axis(2,seq(0,25,2))
> axis(2,seq(0,25,2/10),tcl=-0.2,labels=NA)
>
>
>
>
>
>
> dev.off()
null device
1
>