SDEsim3

The dataset contains discretely sampled observations for a simulated stochastic differential equation (SDE) with dynamics:dX_t = (1.5X_t-0.4X_tY_t)dt+sqrt(0.05X_t)dW_t 
dY_t = (-1.5Y_t+0.4X_tY_t-0.2Y_t^2)dt+sqrt(0.1X_t)dB_t 
where <code>dW_t</code> and <code>dB_t</code> are standard Brownian motions, <code>t</code> is time and <code>X_0 = 5</code>, <code>Y_0 = 5</code>.

datasets

Tools for performing inference and analysis on a class of quadratic diffusion processes for both scalar and bivariate diffusion systems. For scalar diffusions, a module is provided for solving first passage time problems for both time-homogeneous and time-inhomogeneous GQDs.

Etienne AD Pienaar

DiffusionRgqd

Inference and Analysis for Generalized Quadratic Diffusions

SDEsim3 function

A data frame with 1001 observations on the following 3 variables.
 <dl> </dl>

Format

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

dX_t = (1.5X_t-0.4X_tY_t)dt+sqrt(0.05X_t)dW_t 
dY_t = (-1.5Y_t+0.4X_tY_t-0.2Y_t^2)dt+sqrt(0.1X_t)dB_t 


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

SDEsim3: Simulated Stochastic Lotka-Volterra Eqns

Description

Usage

Arguments

Format