Package: cutoffR
Type: Package
Title: CUTOFF: A Spatio-temporal Imputation Method
Version: 1.0
Date: 2013-05-15
Author: Lingbing Feng, Gen Nowak, Alan. H. Welsh, Terry. J. O'Neill
Maintainer: Lingbing Feng <fenglb88@gmail.com>
Description: This package provides a set of tools for spatio-temporal imputation
in R. It includes the implementation for then CUTOFF imputation method,
a useful cross-validation function that can be used not only by the
CUOTFF method but also by some other imputation  functions to help
choosing an optimal value for relevant parameters, such as the number
of k-nearest neighbors for the KNN imputation method, or the number of
components for the SVD imputation method. It also contains tools for
simulating data with missing values with respect to some specific
missing pattern, for example, block missing. Some useful visualisation
functions for imputation purposes are also provided in the package.
LazyLoad: yes
Repository: CRAN
Depends: R (>= 3.1.0)
Imports: ggplot2, reshape2
NeedsCompilation: no
License: GPL-2
Packaged: 2014-05-12 23:50:40 UTC; lingbingfeng
Date/Publication: 2014-05-13 07:44:40

Title: Determine and Evaluate Optimal Cutpoints in Binary
Authors@R: person("Christian", "Thiele", , "c.thiele@hs-osnabrueck.de", c("aut", "cre"))
Description: Estimate cutpoints that optimize a specified metric in binary classification tasks
and validate performance using bootstrapping. Some methods for more robust cutpoint
estimation and various plotting functions are included.
Suggests: KernSmooth (>= 2.23-15), fANCOVA (>= 0.5-1), testthat (>=

Authors@R: person("Christian", "Thiele", , "c.thiele@gmx-topmail.de", c("aut", "cre"))

rmarkdown, mgcv (>= 1.8), crayon (>= 1.3.4)

rmarkdown, mgcv (>= 1.8), crayon (>= 1.3.4), registry (>=

estimation are supported, e.g. a parametric method assuming normal distributions,
bootstrapped cutpoints, and smoothing of the metric values per cutpoint using
Generalized Additive Models. Various plotting functions are included. For an overview
of the package see 'Thiele and Hirschfeld (2020)' <arXiv:2002.09209>.
Author: Christian Thiele [cre, aut] (<https://orcid.org/0000-0002-1156-5117>)