SDEsim2: A Simulated Non-Linear Bivariate Diffusion

In eta21/DiffusionRgqd: Inference and Analysis for Generalized Quadratic Diffusions

Description

The dataset contains discretely sampled observations for a simulated stochastic differential equation (SDE) with dynamics:

dX_t = 2.0(Y_t-X_t)dt+0.3sqrt(X_tY_t)dW_t

dY_t = 1.0(5-Y_t)dt+0.5sqrt(Y_t)dB_t

where dW_t and dB_t are standard Brownian motions, t is time and X_0 = 5, Y_0 = 5.

Usage

data("SDEsim2")

Format

A data frame with 801 observations on the following 3 variables.

Xt

Xt trajectory of the diffusion.

Yt

Yt trajectory of the diffusion.

time

Time vector (time[i+1]-time[i] = 1/8).

Examples

 data(SDEsim2)
  data(SDEsim2)
  attach(SDEsim2)
  # Have a look at the time series:
  plot(Xt~time,type='l',col='blue',ylim=c(2,10),main='Simulated Data',xlab='Time (t)',ylab='State',
       axes=FALSE)
  lines(Yt~time,col='red')
  expr1=expression(dX[t]==2(Y[t]-X[t])*dt+0.3*sqrt(X[t]*Y[t])*dW[t])
  expr2=expression(dX[t]==(5-Y[t])*dt+0.5*sqrt(Y[t])*dB[t])
  text(50,9,expr1)
  text(50,8.5,expr2)
  axis(1,seq(0,100,5))
  axis(1,seq(0,100,5/10),tcl=-0.2,labels=NA)
  axis(2,seq(0,20,2))

eta21/DiffusionRgqd documentation built on May 16, 2019, 8:53 a.m.