killworth: Calculate Killworth Estimates
In NSUM: Network Scale Up Method

Description Usage Arguments Details Value Author(s) References See Also Examples

This function calculates the Killworth estimates for unknown subpopulation sizes based on NSUM data.

1	killworth(dat, known, N)

`dat`	a matrix of non-negagtive integers, the `(i,k)`-th entry represents the number of people that the `i`-th individual knows from the `k`-th subpopulation.
`known`	a vector of positive numbers, the sizes of known subpopulations. All additional columns of `dat` are treated as unknown.
`N`	a positive number, the (known) total population size.

The function killworth allows for the estimation of subpopulation sizes from Killworth's network scale-up model. These estimates can be used to compare with the MCMC results in this package. For reasonable starting values for the MCMC function nsum.mcmc, see the function killworth.start.

A vector of positive numbers with length equal to the number of unknown subpopulations, the Killworth estimates of the subpopulation sizes.

Rachael Maltiel and Aaron J. Baraff

Maintainer: Aaron J. Baraff <ajbaraff at uw.edu>

Killworth, P., Johnsen, E., McCarty, C., Shelley, G., and Bernard, H. (1998a), "A Social Network Approach to Estimating Seroprevalence in the United States," Social Networks, 20, 23-50.

Killworth, P., McCarty, C., Bernard, H., Shelley, G., and Johnsen, E. (1998b), "Estimation of Seroprevalence, Rape, and Homelessness in the United States using a Social Network Approach," Evaluation Review, 22, 289-308.

killworth.start

## load data
data(McCarty)

## simulate from model with barrier effects
sim.bar <- with(McCarty, nsum.simulate(100, known, unknown, N, model="barrier",
                                       mu, sigma, rho))

## estimate unknown population sizes
dat.bar <- sim.bar$y
NK.killworth <- with(McCarty, killworth(dat.bar, known, N))