c(person("Yuri R.", "Fonseca", email="yuriresendefonseca@outlook.com", role = c("aut")),person("Ricardo", "Masini", email="ricardo.masini@fgv.br", role = c("aut")),person("Marcelo C.", "Medeiros", email="mcm@econ.puc-rio.br", role = c("aut")),person("Gabriel F. R.", "Vasconcelos", email="gabrielrvsc@yahoo.com.br", role = c("aut", "cre")))
Gabriel F. R. Vasconcelos <gabrielrvsc@yahoo.com.br>
Set of functions to analyse and estimate Artificial Counterfactual models from Carvalho, Masini and Medeiros (2016) <DOI:10.2139/ssrn.2823687>.
Yuri R. Fonseca [aut],
Ricardo Masini [aut],
Marcelo C. Medeiros [aut],
Gabriel F. R. Vasconcelos [aut, cre]

Package ArDec implements the autoregressive decomposition of a time series based on the constructive approach in West (1997). Particular cases include the extraction of trend and seasonal components from a monthly time series. Uncertainty on the resulting components can be derived from sampling of the autoregressive model which is written as a linear regression model and handled on a Bayesian framework.

Package ArDec implements autoregressive-based decomposition of a time series based on the constructive approach in West (1997). Particular cases include the extraction of trend and seasonal components. Uncertainty on the resulting components can be derived from sampling of the autoregressive model which is written as a linear regression model and handled on a Bayesian framework.

Package ArDec implements autoregressive-based
decomposition of a time series based on the constructive
approach in West (1997). Particular cases include the
extraction of trend and seasonal components.

Autoregressive-based decomposition of a time series based on the approach in West (1997). Particular cases include the extraction of trend and seasonal components.

Bayesian Modeling of Archaeological Chronologies
Anne Philippe [aut, cre],
Marie-Anne Vibet [aut]
c(
person("Anne", "Philippe", role = c("aut", "cre"), email = "anne.philippe@univ-nantes.fr"),
person("Marie-Anne", "Vibet", role = c("aut"))
)
Provides a list of functions for the Bayesian modeling of archaeological chronologies. The Bayesian models are implemented in 'JAGS' ('JAGS' stands for Just Another Gibbs Sampler. It is a program for the analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation. See <http://mcmc-jags.sourceforge.net/> and "JAGS Version 4.3.0 user manual", Martin Plummer (2017) <https://sourceforge.net/projects/mcmc-jags/files/Manuals/>.). The inputs are measurements with their associated standard deviations and the study period. The output is the MCMC sample of the posterior distribution of the event date with or without radiocarbon calibration.
stats, utils, graphics, grDevices, Bchron