Reports repeated values in parameters to identify redundancy before and after folding. This helps assess folding effectiveness and identify remaining optimization potential.
Arguments
- model
A multimod model object (folded or unfolded)
- params
Character vector of parameter names to analyze. If NULL (default), analyzes all parameters with data.
- verbose
Logical; print detailed output (default: TRUE)
- return_details
Logical; return detailed data frame instead of summary (default: FALSE)
Value
If return_details=FALSE, invisibly returns summary data frame. If return_details=TRUE, returns detailed data frame with per-parameter statistics.
Details
For each parameter with data, calculates:
Original redundancy: ratio of repeated values to total rows
Folded redundancy: ratio of repeated values in folded data (if folded)
Compression achieved through folding
Redundancy metrics:
Original redundancy: percentage of rows that have duplicate values (within the full parameter dataset)
Folded redundancy: percentage of rows with duplicate values after folding
Compression ratio: original rows / folded rows
Remaining potential: estimated further compression if all redundancy removed
High original redundancy with no folding indicates missed optimization opportunity. High folded redundancy suggests additional dimensions could be folded.
Examples
if (FALSE) { # \dontrun{
# Analyze all parameters
analyze_parameter_redundancy(model)
# Analyze specific parameters
analyze_parameter_redundancy(model, params = c("pTechCinp2use", "pSupCost"))
# Get detailed results
results <- analyze_parameter_redundancy(model, return_details = TRUE)
View(results)
} # }