ctsmr - Continuous Time Stochastic Modeling in R
Computation
2016-06-02 v1
Abstract
ctsmr is an R package providing a general framework for identifying and estimating partially observed continuous-discrete time gray-box models. The estimation is based on maximum likelihood principles and Kalman filtering efficiently implemented in Fortran. This paper briefly demonstrates how to construct a Continuous Time Stochastic Model using multivariate time series data, and how to estimate the embedded parameters. The setup provides a unique framework for statistical modeling of physical phenomena, and the approach is often called grey box modeling. Finally three examples are provided to demonstrate the capabilities of ctsmr.
Keywords
Cite
@article{arxiv.1606.00242,
title = {ctsmr - Continuous Time Stochastic Modeling in R},
author = {Rune Juhl and Jan Kloppenborg Møller and Henrik Madsen},
journal= {arXiv preprint arXiv:1606.00242},
year = {2016}
}
Comments
11 pages, including R code