Analyze
(Package: RxCEcolInf) :
Workhorse Function for Ecological Inference for Sets of R x C Contingency Tables
This function (using the tuned parameters from Tune) fits a hierarchical model to ecological data in which the underlying contigency tables can have any number of rows or columns. The user supplies the data and may specify hyperprior values. Samples from the posterior distribution are returned as an mcmc object, which can be analyzed with functions in the coda package.
This function (using the tuned parameters from TuneWithExitPoll) fits a hierarchical model to data from two sources: (i) ecological data and in which the underlying contigency tables can have any number of rows or columns, and (ii) data from a survey sample of some of the contingency tables. The user supplies the data and may specify hyperprior values. Samples from the posterior distribution are returned as an mcmc object, which can be analyzed with functions in the coda package.
This function tunes the markov chain monte carlo algorithm used to fit a hierarchical model to data from two sources: (i) ecological data in which the underlying contigency tables can have any number of rows or columns, and (ii data from a survey samlpe of some of the contingency tables. The user supplies the data and may specify hyperprior values. The function's primary output is a vector of multipliers, called rhos, used to adjust the covariance matrix of the multivariate t_4 distribution used to propose new values of intermediate-level parameters (denoted THETAS).
gendata.ep
(Package: RxCEcolInf) :
Function To Simulate Ecological and Survey Data For Use in
This function generates simulated ecological data, i.e., data in the form of contigency tables in which the row and column totals but none of the internal cell counts are observed. At the user's option, data from simulated surveys of some of the ‘units’ (in voting parlance, 'precincts') that gave rise to the contingency tables are also produced.
Tune
(Package: RxCEcolInf) :
Tuning Function for Ecological Inference for Sets of R x C Contingency Tables
This function tunes the markov chain monte carlo algorithm used to fit a hierarchical model to ecological data in which the underlying contigency tables can have any number of rows or columns. The user supplies the data and may specify hyperprior values. The function's primary output is a vector of multipliers, called rhos, used to adjust the covariance matrix of the multivariate t_4 distribution used to propose new values of intermediate-level parameters (denoted THETAS).
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