Title: Interface for FAME time series database
Description: Includes FAME storage and retrieval function, as well as functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.

Packaged: Thu May  1 17:29:31 2008; m1jjh00

Description: Read and write FAME databases.
Packaged: Tue Sep  9 17:31:01 2008; m1jjh00

Title: Interface for FAME Time Series Database

Packaged: Mon Apr 6 13:39:13 2009; m1jjh00

Title: Statistical Tests of Familial Hypotheses
Authors@R: person("Ryan", "Thompson",  email = "ryan.thompson@monash.edu", role = c("aut", "cre"),
Description: Provides functionality for testing familial hypotheses. Currently supports tests of
the Huber family of centers. Testing is carried out using the Bayesian bootstrap. One- and
two-sample tests are supported, as are directional tests. Methods for visualizing output are
Suggests: testthat, knitr, rmarkdown, MASS
Author: Ryan Thompson [aut, cre] (<https://orcid.org/0000-0002-9002-0448>)

Imports: parallel, ggplot2, DepthProc, matrixStats

Description: Provides functionality for testing familial hypotheses. Supports testing centers
belonging to the Huber family. Testing is carried out using the Bayesian bootstrap. One- and

Authors@R: person("Ryan", "Thompson",  email = "ryan.thompson1@unsw.edu.au", role = c("aut", "cre"),

Title: End-to-End Automated Machine Learning and Model Evaluation
person("German Cancer Research Center (DKFZ)", role="cph"))
Description: Single unified interface for end-to-end modelling of regression,
categorical and time-to-event (survival) outcomes. Models created using
familiar are self-containing, and their use does not require additional
information such as baseline survival, feature clustering, or feature
transformation and normalisation parameters. Model performance,
calibration, risk group stratification, (permutation) variable importance,
individual conditional expectation, partial dependence, and more, are
assessed automatically as part of the evaluation process and exported in
tabular format and plotted, and may also be computed manually using export
and plot functions. Where possible, metrics and values obtained during the
evaluation process come with confidence intervals.
Imports: data.table, methods, rlang (>= 0.3.4), rstream, stringi,
Suggests: BART, callr (>= 3.4.3), cluster, CORElearn, cowplot,
dynamicTreeCut, e1071 (>= 1.7.5), Ecdat, fastcluster, ggplot2
(>= 3.0.0), glmnet, gtable, harmonicmeanp, isotree (>= 0.3.0),
knitr, labeling, laGP, MASS, maxstat, mboost (>= 2.9.0),
microbenchmark, partykit, proxy, qvalue, randomForestSRC,
ranger, rmarkdown, scales, testthat (>= 3.0.0), xml2, VGAM,
Author: Alex Zwanenburg [aut, cre] (<https://orcid.org/0000-0002-0342-9545>),
German Cancer Research Center (DKFZ) [cph]