buildmodelmatrix: Build the model matrix based on particular data, as required...
In SparseMSE/sparsemse: Multiple systems estimation for Sparse capture data

Description Usage Arguments Value Examples

This routine builds a model matrix as required by the linear program check checkident and checks if the matrix is of full rank. In addition, for each individual list, and for each pair of lists included in the model, it returns the total count of individuals appearing on the specific list or lists whether or not in combination with other lists.

1	buildmodelmatrix(zdat, mX = NULL)

`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.
`mX`	A 2 \times k matrix giving the k two-list interactions to be included in the model. 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.

A list with components as below

modmat The matrix that maps the parameters in the model (excluding any corresponding to non-overlapping lists) to the log expected value of the counts of capture histories that do not contain non-overlapping pairs in the data.

tvec A vector indexed by the parameters in the model, excluding those corresponding to non-overlapping pairs of lists. For each parameter the vector contains the total count of individuals in all the capture histories that dominate that parameter.

rankdef The column rank deficiency of the matrix modmat. If rankdef = 0, the matrix has full column rank.