bcpmeta-package: Bayesian Multiple Changepoint Detection Using Metadata
In bcpmeta: Bayesian Multiple Changepoint Detection Using Metadata
Description
Details
Author(s)
References
Description
Package for a Bayesian multiple changepoint detection method
to detect mean shifts in AR(1) time series.
It accomodates metadta (if available) by
letting metadata times have higher prior probabilities
to be changepoints.
The changepoint configuration with the highest
posterior probability is the optimal model.
Metropolis-Hastings algorithm is utilized for
quick stochastic search of a potentially huge model space.
This method is ideal for annual series,
since it allows a linear trend component, but not yet monthly cycles.
Details
Package: bcpmeta
Type: Package
Version: 1.0
Date: 2014-05-15
License: GPL(>= 2)
The most important functions of this package:
bcpmeta.model:
find the optimal changepoint configuration,
bcpmeta.parameters:
given a configuration, estimate model parameters.
Author(s)
Yingbo Li
Maintainer: Yingbo Li <ybli@clemson.edu>
References
Li, Y. and Lund, R. (2014) Bayesian Mulitple Changepoint
Detection Using Metadata. (submitted)
bcpmeta documentation built on May 1, 2019, 6:48 p.m.
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Description Details Author(s) References
Description
Package for a Bayesian multiple changepoint detection method to detect mean shifts in AR(1) time series. It accomodates metadta (if available) by letting metadata times have higher prior probabilities to be changepoints. The changepoint configuration with the highest posterior probability is the optimal model. Metropolis-Hastings algorithm is utilized for quick stochastic search of a potentially huge model space. This method is ideal for annual series, since it allows a linear trend component, but not yet monthly cycles.
Details
| Package: | bcpmeta |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2014-05-15 |
| License: | GPL(>= 2) |
The most important functions of this package:
bcpmeta.model:
find the optimal changepoint configuration,
bcpmeta.parameters:
given a configuration, estimate model parameters.
Author(s)
Yingbo Li
Maintainer: Yingbo Li <ybli@clemson.edu>
References
Li, Y. and Lund, R. (2014) Bayesian Mulitple Changepoint Detection Using Metadata. (submitted)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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