pridit (version 1.1.0)

PRIDITscore: Calculate the PRIDIT scores for a ridit matrix

Description

This function takes ridit scores and PRIDIT weights to calculate final PRIDIT scores for each observation.

Usage

PRIDITscore(riditscores, id_vector, weightvec)

Value

A data frame with two columns: "Claim.ID" containing the IDs and "PRIDITscore" containing the calculated PRIDIT scores (ranging from -1 to 1).

Arguments

riditscores

A data frame where the first column represents IDs. The IDs uniquely identify each row in the matrix. The remaining columns contain the ridit scores for each ID.

id_vector

A vector of IDs corresponding to the observations.

weightvec

A numeric vector of PRIDIT weights (from PRIDITweight function).

References

Brockett, P. L., Derrig, R. A., Golden, L. L., Levine, A., & Alpert, M. (2002). Fraud classification using principal component analysis of RIDITs. Journal of Risk and Insurance, 69(3), 341-371.

Examples

# Complete workflow example
test_data <- data.frame(
  ID = c("A", "B", "C", "D", "E"),
  var1 = c(0.9, 0.85, 0.89, 1.0, 0.89),
  var2 = c(0.99, 0.92, 0.90, 1.0, 0.93),
  var3 = c(1.0, 0.99, 0.98, 1.0, 0.99)
)

# Step 1: Calculate ridit scores
ridit_result <- ridit(test_data)

# Step 2: Calculate PRIDIT weights
weights <- PRIDITweight(ridit_result)

# Step 3: Calculate final PRIDIT scores
final_scores <- PRIDITscore(ridit_result, test_data$ID, weights)
print(final_scores)