Collate: 'data.R' 'geom_qq_band.R' 'qqplotr.R' 'runShinyExample.R'
Suggests: shiny, devtools, lattice, shinyBS

Imports: dplyr, MASS, knitr, purrr, robustbase, rmarkdown

Authors@R: c(person("Alexandre", "Almeida", email = "almeida.xan@gmail.com", role = c("aut")),
person("Adam", "Loy", email = "loyad01@gmail.com", role = c("aut", "cre")),

Suggests: shiny, devtools, lattice, shinyBS, knitr, rmarkdown

Title: Quantile-quantile analysis of 24-hr precipitation using a frame
work based on the exponential distribution
Depends: ncdf, fields, clim.pact, akima, LatticeKrig, PrecipStat, R (>=
Description: The package provides a quick analysis of quantiles of
wet-day 24-hr accumulated precipitation records, demonstrating
that the quantiles to a great degree can be predicted from the
wet-day mean. The package analyses both observations and

Depends: ncdf, fields, clim.pact, akima, LatticeKrig, PrecipStat, evd,

Title: Data from Brazilian Soccer Championship
Description: Get data about the Brazilian soccer championship since 2014. Official data can
Depends: xml2, rvest, tidyverse, dplyr, stringr, R (>= 2.10)

Package: qqtest
Type: Package
Title: Quantile Quantile Plots Self Calibrating For Visual Testing
Version: 1.0
Date: 2014-12-02
Authors@R: person("Wayne", "Oldford", email="rwoldford@uwaterloo.ca",
role=c("aut", "cre"))
Maintainer: Wayne Oldford <rwoldford@uwaterloo.ca>
Description: Provides the function qqtest which incorporates uncertainty in its
qqplot display(s) so that the user might have a better sense of the
evidence against the specified distributional hypothesis.  qqtest draws a
quantile quantile plot for visually assessing whether the data come from a
test distribution that has been defined in one of many ways.  The vertical
axis plots the data quantiles, the horizontal those of a test distribution.
The default behaviour generates 1000 samples from the test distribution and
overlays the plot with pointwise interval estimates for the ordered
quantiles from the test distribution.  A small number of independently
generated exemplar quantile plots are also overlaid.  Both the interval
estimates and the exemplars provide different comparative information to
assess the evidence provided by the qqplot for or against the hypothesis
that the data come from the test distribution (default is normal or
gaussian).  Finally, a visual test of significance (a lineup plot) can also
be displayed to test the null hypothesis that the data come from the test
distribution.
License: GPL-3
Depends: R (>= 2.10.0)
Imports: grDevices, MASS
Packaged: 2014-12-13 19:36:06 UTC; rwoldford
Author: Wayne Oldford [aut, cre]
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-12-14 01:15:35