ComputeIntervals: Function for calculating intervals for suppressed tables.

Description

This function solves linear programs to determine interval boundaries for suppressed cells.

Usage

ComputeIntervals(
  x,
  z,
  primary,
  suppressed,
  minVal = NULL,
  lpPackage = "lpSolve",
  gaussI = TRUE,
  allInt = FALSE,
  sparseConstraints = TRUE
)

Arguments

x: ModelMatrix, as output from SSBtools::ModelMatrix
z: numerical vector with length ncol(x). Corresponds to table cell values
primary: Vector indicating primary suppressed cells. Can be logical or integer. If integer vector, indicates the columns of x which are considered primary suppressed.
suppressed: Vector indicating all suppressed cells. Can be logical or integer. If integer vector, indicates the columns of x which are considered suppressed.
minVal: a known minimum value for table cells. Default NULL. Note that 'minVal' is interpreted as the limiting value for all suppressed cells. Specifying 'minVal=0' would be redundant, as a minimum value of 0 is anyway assumed for inner cells (see details).
lpPackage: The name of the package used to solve linear programs. Currently, 'lpSolve' (default), 'Rsymphony', 'Rglpk' and 'highs' are supported.
gaussI: Boolean vector. If TRUE (default), GaussIndependent is used to reduce size of linear program.
allInt: Integer variables when TRUE. See all.int parameter in lpSolve and types parameter in Rsymphony and Rglpk.
sparseConstraints: When TRUE, a sparse constraint matrix will be input to the solver. In the case of lpSolve, the sparse matrix is represented in triplet form as a dense matrix with three columns, and the dense.const parameter is utilized.

Author

Øyvind Langsrud and Daniel Lupp

Details

This function is still experimental.

Default in for bounds parameter in Rsymphony_solve_LP and Rglpk_solve_LP: The default for each variable is a bound between 0 and Inf. Details in lpSolve: Note that every variable is assumed to be >= 0!