Packaged: Tue Dec  9 14:17:34 2008; zeileis

Description: Exchange rate regression and structural change tools for
estimating, testing, dating, and monitoring (de facto) exchange

Author: Achim Zeileis, Ajay Shah, Ila Patnaik, Anmol Sethy

person(given = "Ajay", family = "Shah", role = "ctb"),
person(given = "Ila", family = "Patnaik", role = "ctb"),
person(given = "Anmol", family = "Sethy", role = "ctb"))
Depends: R (>= 2.10.0), graphics, stats, zoo, sandwich, strucchange

Depends: R (>= 2.14.0), zoo, strucchange

Title: Feature Extraction from Grouped Data
Description: An R6 implementation for calculating features from grouped data.
The output will be one row for each group.
This functionality is often needed in the feature extraction process of machine learning problems.
Very large datasets are supported, since data is only read into RAM when needed.
Calculation can be done in parallel and the process can be monitored.
Results are available in one final dataframe.
Authors@R: c(person("Quay", "Au", email = "quayau@gmail.com", role = c("aut", "cre")),
person("Clemens", "Stachl", email = "clemensstachl@gmail.com", role = "ctb"),
person("Ramona", "Schoedel", email = "ramonaschoedel90@gmail.com", role = "ctb"),
person("Theresa", "Ullmann", email = "theresa_ullmann@gmx.de", role = "ctb"),
person("Andreas", "Hofheinz", email = "andreas.hofheinz@outlook.com", role = "ctb")
Imports: dplyr, magrittr, checkmate, utils, data.table, future,
Suggests: testthat, knitr, covr, pkgdown

Imports: dplyr, magrittr, checkmate, data.table, future.apply, R6, fs
Suggests: testthat, knitr, covr, utils, future, pkgdown

Imports: dplyr, magrittr, checkmate, data.table, future.apply, R6

Description: In Australia, a financial year (or fiscal year) is the period from 1 July to 30 June
of the following calendar year. As such, many databases need to represent and
validate financial years efficiently. While the use of integer years with a convention that
they represent the year ending is common, it may lead to ambiguity with calendar years.
On the other hand, string representations may be too inefficient and do not easily admit
arithmetic operations. This package tries to make validation of financial years quicker while
Imports: fastmatch, data.table, hutils, utils
Suggests: testthat, withr, rlang, zoo, covr