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Create a table checking different optimization solution conditions for each grouping in the data.

Usage

check_solution(dt, solution_qx_col, by_vars)

Arguments

dt

[data.table()]
Collection of life tables from a single location, with columns representing the betas and optomized qx solution.

solution_qx_col

[character(1)]
Column name of dt containing the optimized qx solution. There is expected to be only one unique value by group.

by_vars

[character()]
Column names in dt uniquely identifying a life table.

Value

[data.table()]

Table including by_vars and columns for each condition checked.

Details

The conditions checked are:

  1. Is the solution qx >= the qx of the preceding age group?

  2. Is the solution qx < 1?

  3. Is the implied terminal qx < 1?