Authors@R: c(person("Pein", "Florian", role = c("aut", "cre"), email = "fp366@cam.ac.uk"),

Imports: stepR (>= 2.1.0), lowpassFilter, stats, methods
Suggests: testthat, R.cache (>= 0.10.0), R.rsp
Description: Implements the model-free multiscale idealisation approaches: Jump-Segmentation by MUltiResolution Filter (JSMURF) <doi:10.1109/TNB.2013.2284063>, JUmp Local dEconvolution Segmentation filter (JULES) <doi:10.1109/TNB.2018.2845126> and Heterogeneous Idealization by Local testing and DEconvolution (HILDE) <arXiv:2008.02658>. Further details on how to use them are given in the accompanying vignette.

Authors@R: c(person("Pein", "Florian", role = c("aut", "cre"), email = "f.pein@lancaster.ac.uk"),

Description: Get description of images from Clarifai API. For more information,
see http://clarifai.com. Clarifai uses a large deep learning cloud to come
up with descriptive labels of the things in an image. It also provides how
confident it is about each of the labels.

see <http://clarifai.com>. Clarifai uses a large deep learning cloud to come

Title: Distribution-Free Tests of Non-Nested Models
Description: Implementation of Clarke's distribution-free test of
non-nested models.  Currently supported model functions are:
lm(), glm() ('binomial', 'poisson', 'negative binomial' links),
polr() ('MASS'), clm() ('ordinal'), and multinom() ('nnet').
For more information on the test, see Clarke (2007)

R port by Brian Ripley <ripley@stats.ox.ac.uk>.
Description: Various functions for classification.

person("William", "Venables", role = "cph"))

Description: Various functions for classification, including k-nearest
neighbour, Learning Vector Quantization and Self-Organizing Maps.

Copyright: W. N. Venables and B. D. Ripley

Title: Construct Graph of S4 Class Hierarchies
Author: Martin Maechler partly based on code from Robert Gentleman
Description: Construct directed graphs of S4 class hierarchies and
visualize them.  Typically, these graphs are DAGs (directed acyclic
Packaged: Thu Jun 28 15:06:19 2007; maechler