R Graphical Manual

Last data update: 2014.03.03

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Results 1 - 7 of 7 found.
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tsbugs-package (Package: tsbugs) :

The tsbugs package contains a collection of R functions that can be used to create time series BUGS models of various order. Included are function to create BUGS with non-constant variance such stochastic volatility models and random variance shift models.

● Data Source: CranContrib
● Keywords:
● Alias: tsbugs, tsbugs-package
● 0 images

sv.bugs (Package: tsbugs) :

Create BUGS script of an SV time series model, similar those in Meyer and Yu (2002). Options allow for the inclusion of a different lag orders for the mean term, forecasts, posterior simulations from the model and alternative specification of prior distributions on each parameters.

● Data Source: CranContrib
● Keywords:
● Alias: sv.bugs
● 0 images

rv.bugs (Package: tsbugs) :

Create BUGS script of an Random Variance (RV) shift model similar to that of McCulloch and Tsay (1991). Options allow for the inclusion of a different lag orders for the mean term, forecasts, posterior simulations from the model and alternative specification of prior distributions on some parameters.

● Data Source: CranContrib
● Keywords:
● Alias: rv.bugs
● 0 images

print.tsbugs (Package: tsbugs) :

Prints the BUGS model in a tsbugs object.

● Data Source: CranContrib
● Keywords:
● Alias: print.tsbugs
● 0 images

nodes (Package: tsbugs) :

Provides a data.frame of both random and deterministic nodes in a tsbugs BUGS model. Can also be used to extract nodes from just a single part of the model, such as the prior distributions. This might be of particular use to users when setting up parameters to follow when running models through R2WinBUGS or R2OpenBUGS.

● Data Source: CranContrib
● Keywords:
● Alias: nodes
● 0 images

inits (Package: tsbugs) :

Creates a list of initial values for a tsbugs object to help shorten your code when running models through R2WinBUGS or R2OpenBUGS.

● Data Source: CranContrib
● Keywords:
● Alias: inits
● 0 images

ar.bugs (Package: tsbugs) :

Create BUGS script of an time series model, where the data is assumed to be normally distributed. Options allow for the inclusion of a different lag orders for the mean term, forecasts, posterior simulations from the model and alternative specification of prior distributions on each parameter.

● Data Source: CranContrib
● Keywords:
● Alias: ar.bugs
● 0 images