postN0: Posterior mean, median, and mode for the number of...
In MobilePhoneESSnetBigData/pestim: Population Estimations Using Mobile Phone Data

Description Usage Arguments Details Value See Also Examples

Compute the posterior mean, median, and mode for the number of individuals generating posterior distribution according to the hierarchical model at the initial time instant

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postN0(nMNO, nReg, fu, fv, flambda, n = 1000, scale = 1, relTol = 1e-08,
  nSim = 1000, nStrata = c(1, 100), verbose = FALSE,
  nThreads = RcppParallel::defaultNumThreads(), alpha = 0.05)

`nMNO,`	nReg non-negative integer vectors with the number of individuals detected in each cell according to the network operator and the register
`fu,`	fv named lists with the prior marginal distributions of the two-dimensional points for the Monte Carlo integration
`flambda`	named list with the prior distribution of the lambda parameter
`n`	number of points to generate in the posterior distribution for the computation. Default value is 1e3
`scale`	numeric vector with the scale to count the number of individuals. Default value is 1
`relTol`	relative tolerance in the computation of the `kummer` function. Default value is `1e-6`
`nSim`	number of two-dimensional points to generate to compute the integral. Default value is `1e4`
`nStrata`	integer vector of length 2 with the number of strata in each dimension. Default value is `c(1, 1e2)`
`verbose`	logical (default `FALSE`) to report progress of the computation
`nThreads`	number (default the number of all cores, including logical cores) to use for computation
`alpha`	the significance level for accuracy measures. Default value is 0.05

The prior distributions are specified as named lists where the first component of each list must be the name of distribution ('unif', 'triang', 'degen', 'gamma') and the rest of components must be named according to the name of the parameters of the random generator of the corresponding distribution according to:

unif: xMin, xMax for the minimum, maximum of the sampled interval.
degen: x0 for the degenerate value of the random variable.
triang: xMin, xMax, xMode for minimum, maximum and mode (see qtriang).
gamma: scale and shape with the same meaning as in rgamma.

postN0 computes the posterior mean, median, and mode of the posterior distribution for each cell. The function returns a matrix with the estimates in columns and the cells in rows.

rN0

# It takes a couple of minutes
postN0(nMNO = 20, nReg = 115, fu = list('unif', xMin = 0.3, xMax = 0.5),
        fv = list('unif', xMin = 100, xMax = 120),
        flambda = list('gamma', shape = 11, scale = 12))