- ard
The `n_i x n_k` matrix of non-negative ARD integer responses,
where the `(i,k)th` element corresponds to the number of people that
respondent `i` knows in subpopulation `k`.
- known_sizes
The known subpopulation sizes corresponding to a subset of
the columns of ard.
- known_ind
The indices that correspond to the columns of ard
with known_sizes. By default, the function assumes the first n_known
columns, where n_known corresponds to the number of
known_sizes.
- G1_ind
A vector of indices denoting the columns of `ard` that
correspond to the primary scaling groups, i.e. the collection of rare
girls' names in Zheng, Salganik, and Gelman (2006). By default, all
known_sizes are used. If G2_ind and B2_ind are not provided, `C = C_1`, so
only G1_ind are used. If G1_ind is not provided, no scaling is performed.
- G2_ind
A vector of indices denoting the columns of `ard` that
correspond to the subpopulations that belong to the first secondary scaling
groups, i.e. the collection of somewhat popular girls' names.
- B2_ind
A vector of indices denoting the columns of `ard` that
correspond to the subpopulations that belong to the second secondary
scaling groups, i.e. the collection of somewhat popular boys' names.
- N
The known total population size.
- warmup
A positive integer specifying the number of warmup samples.
- iter
A positive integer specifying the total number of samples
(including warmup).
- refresh
An integer specifying how often the progress of the sampling
should be reported. By default, resorts to every 10
verbose = FALSE.
- thin
A positive integer specifying the interval for saving posterior
samples. Default value is 1 (i.e. no thinning).
- verbose
Logical value, specifying whether sampling progress should be
reported.
- alpha_tune
A positive numeric indicating the standard deviation used
as the jumping scale in the Metropolis step for alpha. Defaults to 0.4,
which has worked well for other ARD datasets.
- beta_tune
A positive numeric indicating the standard deviation used as
the jumping scale in the Metropolis step for beta Defaults to 0.2, which
has worked well for other ARD datasets.
- omega_tune
A positive numeric indicating the standard deviation used
as the jumping scale in the Metropolis step for omega Defaults to 0.2,
which has worked well for other ARD datasets.
- init
A named list with names corresponding to the first-level model
parameters, name 'alpha', 'beta', and 'omega'. By default the 'alpha' and
'beta' parameters are initialized at the values corresponding to the
Killworth MLE estimates (for the missing 'beta'), with all 'omega' set to
20. Alternatively, init = 'random' simulates 'alpha' and 'beta' from
a normal random variable with mean 0 and standard deviation 1. By default,
init = 'MLE' initializes values at the Killworth et al. (1998b) MLE
estimates for the degrees and sizes and simulates the other parameters.