Title: Quantitative Polymerase Chain Reaction (qPCR) Data Mining and
Imports: bcp, changepoint, caret, chipPCR, ecp, fda.usc, FFTrees,
magrittr, MBmca, pbapply, plotly, pracma, qpcR, robustbase,
randomForest, stats, testthat, utils, visdat, zoo
Suggests: data.table, dplyr, knitr, RDML, readxl, rmarkdown, xtable

Description: Extracts features from amplification curve data of quantitative Polymerase Chain Reactions (qPCR) (Pabinger S. et al. (2014) <doi:10.1016/j.bdq.2014.08.002>) for machine learning purposes. Helper functions prepare the amplification curve data for processing as functional data (e.g., Hausdorff distance) or enable the plotting of amplification curve classes (negative, ambiguous, positive). The hookreg() and hookregNL() functions (Burdukiewicz M. et al. (2018) <doi:10.1016/j.bdq.2018.08.001>) can be used to predict amplification curves with an hook effect-like curvature. The pcrfit_single() function can be used to extract features from an amplification curve.
Imports: bcp, changepoint, chipPCR, ecp, fda.usc, MBmca, pbapply,
pracma, qpcR, robustbase, shiny, stats, utils, zoo
Suggests: DT, FFTrees, knitr, RDML, randomForest, readxl, rmarkdown,

spelling, testthat, xtable, future, listenv

Description: Extracts features from amplification curve data of quantitative
Polymerase Chain Reactions (qPCR) (Pabinger S. et al. (2014)
<doi:10.1016/j.bdq.2014.08.002>) for machine learning purposes. Helper
functions prepare the amplification curve data for processing as functional
data (e.g., Hausdorff distance) or enable the plotting of amplification
curve classes (negative, ambiguous, positive). The hookreg() and hookregNL()
can be used to predict amplification curves with an hook effect-like
curvature. The pcrfit_single() function can be used to extract features
pracma, qpcR, robustbase, segmented, shiny, stats, utils, zoo
Suggests: DT, future, knitr, listenv, RDML, readxl, rmarkdown,

Title: Calculate the probability of correct selection (PCS)
Description: Given k populations (can be in thousands), what is the
probability that a given subset of size t contains the true top
t populations?  This package finds this probability and offers
three tuning parameters (G, d, L) to relax the definition.