Package: AtelieR
Type: Package
Title: A GTK GUI for teaching basic concepts in statistical inference,
and doing elementary bayesian tests.
Version: 0.23
Encoding: UTF-8
Date: 2012-10-27
Author: Yvonnick Noel, University of Brittany, France
Maintainer: Yvonnick Noel <yvonnick.noel@uhb.fr>
Description: A collection of statistical simulation and computation
tools with a GTK GUI, to help teach statistical concepts and
compute probabilities. Two domains are covered: I.
Understanding (Central-Limit Theorem and the Normal
Distribution, Distribution of a sample mean, Distribution of a
sample variance, Probability calculator for common
distributions), and II. Elementary Bayesian Statistics
(bayesian inference on proportions, contingency tables, means
and variances, with informative and noninformative priors).
License: GPL (>= 2)
Depends: R (>= 2.10), proto, cairoDevice, gWidgetsRGtk2, partitions
Packaged: 2012-11-21 22:44:45 UTC; noel
Repository: CRAN
Date/Publication: 2012-11-22 09:53:15

Title: Download Air Quality and Meteorological Information of Chile
Authors@R: c(person("Francisco", "Catalan Meyer", email = "francisco.catalan@ug.uchile.cl",
person("Manuel", "Leiva", email = "MANLEIVA@uchile.cl",
person("Richard", "Toro", email = "rtoro81@uchile.cl",
Maintainer: Francisco Catalan Meyer <francisco.catalan@ug.uchile.cl>
Description: Download air quality and meteorological information of Chile from  the National Air Quality System (S.I.N.C.A.)<https://sinca.mma.gob.cl/> dependent on the Ministry of the Environment and the Meteorological Directorate of Chile (D.M.C.)<http://www.meteochile.gob.cl/> dependent on the Directorate General of Civil Aeronautics.
Author: Francisco Catalan Meyer [aut, cre]

Imports: data.table, plotly, shiny, openair, lubridate,

Title: Acoustic Traveltime Calculations for 1-D Atmospheric Models
Description: Calculates acoustic traveltimes and ray paths in 1-D,
linear atmospheres.  Later versions will support arbitrary 1-D
atmospheric models, such as radiosonde measurements and

Title: Data Augmentation for Machine Learning on Tabular Data
Maintainer: Rafael S. Pereira <r.s.p.models@gmail.com>
Description: Implementation of a data augmentation technique based on conditional entropy
It was devised by both authors during their masters and is discussed in detail in the second author dissertation.
It is able to create novel samples conditioned on a desired value of a categorical attribute, as a way to augment data for classification tasks
Tests discussed in the dissertation and future paper present that the technique satisfies several statistical assumptions for the novel samples.
It also shows significant improvement for machine learning models trained on small data.
Author: Rafael S. Pereira [aut, cre, cph],
Henrique Matheus ferreira da silva [aut, cph],