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Check extended-MLE conditions for multiple data vectors and models

check_extended_MLE_batch.Rd

Suppose we have a vector of models and a collection of different data outcomes on the same set of capture histories. Typically, these will be bootstrap replications. This routine carries out the extended-MLE checks for every combination of data outcome and model. It economises the task of determining which model/data combinations satisfy both the identifiability and Fienberg–Rinaldo conditions by first finding the unique support patterns among the data outcomes.

Usage

check_extended_MLE_batch(x, xcap, zmods)

Arguments

x

Numeric matrix whose columns contain count vectors for a common set of capture histories.

xcap

Binary matrix defining the capture histories corresponding to the rows of x.

zmods

Named list of encoded effect vectors, or a character vector of hierarchy strings.

Value

A logical matrix with models in rows and data vectors in columns. An element is TRUE when both extended-MLE conditions are satisfied for that model and support pattern.

References

Silverman, B. W., Chan, L. and Vincent, K., (2024). Bootstrapping Multiple Systems Estimates to Account for Model Selection Statistics and Computing, 34, 44, doi:10.1007/s11222-023-10346-9 .