rOU: Generate data from invariant distribution of O-U process

In gherardovarando/crossSectional: Estimate Dynamical Model from Cross Sectional Data

Description

Sample observations from the invariant distribution of an Ornstein-Uhlenbeck process:

dX_t = B(X_t - μ)dt + DdW_t

Usage

rOU(n = 1, B, D = diag(nrow = nrow(B), ncol = ncol(B)), mean = rep(0,
  nrow(B)))

Arguments

n	number of sample
B	square matrix, coefficients of the O-U equation
D	noise matrix
mean	invariant mean

Value

A list with components:

• sample the produced sample

• Sigma the covariance matrix of the invariant distribution

• C the C matrix

• B the coefficient square matrix

• mean the mean vector of the invariant distribution

gherardovarando/crossSectional documentation built on July 7, 2019, 12:44 a.m.