Rdrw {Rdrw} | R Documentation |
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.