# Reference Interval Estimation using Real-World Data

## Documentation for package ‘refineR’ version 1.6.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

refineR-package | refineR: Reference Interval Estimation using Real-World Data (RWD)
addGrid | Add a grid to an existing plot.
as.rgb | Convert color-names or RGB-code to possibly semi-transparent RGB-code.
ashDensity | Estimate density of distribution employing the R package "ash" using R-wrapper function.
BoxCox | One-parameter Box-Cox transformation.
calculateCostHist | Calculate costs for a specific combinations of lambda, muVec and sigmaVec.
defineSearchRegions | Helper function to define search regions for mu and sigma and to get the region around the main peak 'ab'
estimateAB | Helper function to find region around the main peak of a distribution
findMainPeak | Helper function to find the main peak of a distribution
findPeaksAndValleys | Find the index of the peaks and valleys of the density estimation.
findRI | Function to estimate reference intervals for a single population
findRoundingBase | Estimate rounding base of the input data.
generateHistData | Generate list with histogram data.
getRI | Method to calculate reference intervals (percentiles) for objects of class 'RWDRI'
getSumForPArea | Helper function to calculate the amount of observed and estimated data points within specified regions around the peak.
invBoxCox | Inverse of the one-parameter Box-Cox transformation.
optimizeGrid | Helper function for grid search for mu and sigma.
plot.RWDRI | Standard plot method for objects of class 'RWDRI'
pnormApprox | Approximate calculation of CDF of normal distribution.
print.RWDRI | Standard print method for objects of class 'RWDRI'
refineR | refineR: Reference Interval Estimation using Real-World Data (RWD)
testcase1 | Simulated Testcase 1.
testcase2 | Simulated Testcase 2.
testcase3 | Simulated Testcase 3.
testcase4 | Simulated Testcase 4.
testcase5 | Simulated Testcase 5.
testParam | Helper function to find optimal parameters lambda, mu and sigma.