estimatepopulation: Estimate the total population including the dark figure

In SparseMSE/sparsemse: Multiple systems estimation for Sparse capture data

Description

This routine calculates the estimate of the total population, including the dark figure, together with confidence intervals as specified. It also returns the details of the fitted model.

Usage

estimatepopulation(zdat, method = "stepwise", quantiles = c(0.025,
  0.975), mX = NULL, pthresh = 0.001)

Arguments

zdat	Data matrix with t+1 columns. The first t columns, each corresponding to a particular list, are 0s and 1s defining the capture histories observed. The last column is the count of cases with that particular capture history. List names A, B, ... are constructed if not supplied. Where a capture history is not explicitly listed, it is assumed that it has observed count zero.
quantiles	Quantiles of interest for confidence intervals.
mX	A 2 \times k matrix giving the k two-list interactions to be included in the model if method = "fixed". Each column of mX contains the numbers of the corresponding pair of lists. If mX = 0, then all two-list interactions are included. If mX = NULL, no interactions are included and the main effects model is fitted. If only one interaction is to be fitted, it is ok to specify it as a vector of length 2, e.g mX=c(1,3) for interactions of list 1 and 3. If method is equal to "stepwise" or "fixed" then mX is ignored.
pthresh	Threshold p-value used if method = "stepwise".

Value

A list of components as below

estimate Point estimate and confidence interval estimates corresponding to specified quantiles

MSEfit The model fitted to the data in the format described in modelfit.

Examples

data(NewOrl)
data(NewOrl_5)
estimatepopulation(NewOrl, method="stepwise", quantiles=c(0.025,0.975))
estimatepopulation(NewOrl_5, method="main", quantiles=c(0.01, 0.05,0.95, 0.99))

SparseMSE/sparsemse documentation built on May 7, 2019, 7:13 p.m.