dajmcdon/spasm: Implements the Laplace-Gaussian filter for sparse, additive, state-space models
Version 0.1

Estimates semi-parametric high-dimensional state-space models. Here we presume that both the observation and state distributions have Gaussian noise, but we let the observation equation evolve as an additive model in the state. In particular, we expand the state in the spline basis and estimate the coefficients via the group lasso. As this model is non-linear, we use the Laplace-Gaussian filter to estimate the hidden states quickly and accurately.

Getting started

Package details

Maintainer
LicenseGPL
Version0.1
URL http://github.iu.edu/dajmcdon/spasm
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("dajmcdon/spasm")
dajmcdon/spasm documentation built on July 28, 2017, 5:26 a.m.