Title: Rigorous Data Reduction and Error Propagation of Ar40 / Ar39
Description: Processes noble gas mass spectrometer data to determine the isotopic composition of argon (comprised of Ar36, Ar37, Ar38, Ar39 and Ar40) released from neutron-irradiated potassium-bearing minerals. Then uses these compositions to calculate precise and accurate geochronological ages for multiple samples as well as the covariances between them. Error propagation is done in matrix form, which jointly treats all samples and all isotopes simultaneously at every step of the data reduction process. Includes methods for regression of the time-resolved mass spectrometer signals to t=0 ('time zero') for both single- and multi-collector instruments, blank correction, mass fractionation correction, detector intercalibration, decay corrections, interference corrections, interpolation of the irradiation parameter between neutron fluence monitors, and (weighted mean) age calculation. All operations are performed on the logs of the ratios between the different argon isotopes so as to properly treat them as 'compositional data', sensu Aitchison [1986, The Statistics of Compositional Data, Chapman and Hall].
Imports: utils, stats, methods, graphics, grDevices

Authors@R: 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")))
Maintainer: Gabriel F. R. Vasconcelos <gabrielrvsc@yahoo.com.br>
Description: Set of functions to analyse and estimate Artificial Counterfactual models from Carvalho, Masini and Medeiros (2016) <DOI:10.2139/ssrn.2823687>.
Packaged: 2017-04-03 22:03:15 UTC; gabrielrvsc

Packaged: 2017-04-19 18:37:19 UTC; gabrielrvsc

Packaged: 2017-07-19 16:21:25 UTC; gabrielrvsc

Packaged: 2017-11-05 12:21:25 UTC; gabrielrvsc

Title: Time series autoregressive decomposition
Maintainer: S. M. Barbosa <susana.barbosa@fc.up.pt>
Description: 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.
Packaged: Tue Oct 11 17:38:00 2005; susana