modelCheckInd: Indicators for model checking.

In MobilePhoneESSnetBigData/pestim: Population Estimations Using Mobile Phone Data

Description

Compute the indicators for model checking given by ...

Usage

modelCheckInd(nSimPar, nMNO, nReg, fu, fv, flambda, relTol = 1e-06,
  nSim = 1e+06, nStrata = c(1, 100, 100), verbose = FALSE,
  nThreads = RcppParallel::defaultNumThreads())

Arguments

nSimPar	number of simulations to compute the underlying integrals
nMNO	non-negative integer vectors with the number of individuals detected according to the network operator
nReg	non-negative integer vectors with the number of individuals detected according to the population register
fu	named list with the prior marginal distribution of the parameter u
fv	named list with the prior marginal distributions of the parameter v
flambda	named list with the prior distribution of the parameter λ
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 1e6
nStrata	integer vector of length 3 with the number of strata in each dimension. Default value is c(1, 1e2, 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

Details

The underlying integrals are computed using with Monte Carlo techniques using nSimPar points for each of the generated random deviate values.

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 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.

• triang: xMin, xMax, xMode for minimum, maximum and mode (see qtriang).

• gamma: scale and shape with the same meaning as in rgamma.

Value

modelCheckInd returns a data.table with the values of the indicators for model checking:

• nMNO:

• nReg:

• B:

• relB:

• V:

• relV:

• MSE:

• relMSE:

References

https://github.com/MobilePhoneESSnetBigData

See Also

rNMNOrep

Examples

# Easily, a function to draw conditioned on the parameters:
modelCheckInd(nSimPar = 10, nMNO = 29, nReg = 123, 
         fu = list('unif', xMin = 0.2, xMax = 0.25),
         fv = list('unif', xMin = 115, xMax = 130),
         flambda = list('gamma', shape = 21, scale = 123 / 20))

modelCheckInd(nSimPar = 10, nMNO = c(29, 31), nReg = c(123, 119), 
         fu = list(list('unif', xMin = 0.2, xMax = 0.25),
                   list('unif', xMin = 0.21, xMax = 0.26)),
         fv = list(list('unif', xMin = 115, xMax = 130),
                   list('unif', xMin = 114, xMax = 131)),
         flambda = list(list('gamma', shape = 21, scale = 123 / 20),
                        list('gamma', shape = 11, scale = 124 / 10)))
                        

MobilePhoneESSnetBigData/pestim documentation built on May 31, 2019, 2:44 p.m.