Rdrw-package: Univariate and Multivariate Damped Random Walk Processes

In Rdrw: Univariate and Multivariate Damped Random Walk Processes

Description

The R package Rdrw provides a toolbox to fit and simulate univariate and multivariate damped random walk processes, possibly with known measurement error standard deviations via state-space representation. The damped random walk process is also known as an Ornstein-Uhlenbeck process or a continuous-time auto-regressive model with order one, i.e., CAR(1) or CARMA(1, 0). The package Rdrw adopts Kalman-filtering to evaluate the resulting likelihood function of the model parameters, leading to a linear complexity in the number of unique observation times. The package provides two functionalities; (i) it fits the model and returns the maximum likelihood estimates or posterior samples of the model parameters; (ii) it simulates time series data following the univariate or multivariate damped random walk process.

Details

Package:	Rdrw
Type:	Package
Version:	1.0.2
Date:	2020-9-8
License:	GPL-2
Main functions:	drw, drw.sim

Author(s)

Zhirui Hu and Hyungsuk Tak

References

Zhirui Hu and Hyungsuk Tak (2020+), "Modeling Stochastic Variability in Multi-Band Time Series Data," arXiv:2005.08049.

Rdrw documentation built on Sept. 9, 2020, 1:06 a.m.