The new version includes the following updates and improvements:

Using the truncated normal distribution now as basic model assumption

Additional regularization term in cost function to control the fit at the tails of the distribution

The median bootstrapping model (pointEst=“medianBS”) now corresponds to one parametric model selected from all bootstrapping models

Some modifications in plot function, e.g. adjusted default

`xlim`

Slight modification of print function

RIbench benchmark score: 0.307, Failure rate: 0.0, Implausible Results: 0.122%

The new version includes the following updates and improvements:

Adjusted computation of the

`roundingBase`

to now also handle data not rounded to power of 10 (e.g. data that was rounded prior to unit conversion)Vignette (‘refineR_package’) demonstrating the main functions of the package

RIbench benchmark score: 0.307, Failure rate: 0.0, Implausible Results: 0.625%

The new version includes the following updates and improvements:

More fine-grained search region for lambda (

`lambdaVec`

)Option to use the two-parameter (modified) Box-Cox transformation (

`findRI(Data = Data, model = "modBoxCox")`

)Update of calculation of costs: new factor to account for small deviations from the assumption of a unimodal distribution of non-pathological samples

Adapted definition of region of test results that characterizes the non-pathological distribution

Improved performance for skewed distributions

RIbench benchmark score: 0.307, Failure rate: 0.0, Implausible Results: 0.625%

Detailed description can be found in Ammer, T., Ammer, T.,Schuetzenmeister, A., Prokosch, HU., Zierk, J., Rank, C.M., Rauh, M. RIbench: A Proposed Benchmark for the Standardized Evaluation of Indirect Methods for Reference Interval Estimation. Clinical Chemistry (2022)

Initial version put on CRAN

Detailed description of the method can be found in Ammer, T., Schuetzenmeister, A., Prokosch, HU., Rauh, M., Rank, C.M., Zierk, J. refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data. Sci Rep 11, 16023 (2021).