heaviness: Heaviness from parent packages

CRAN

pkgndep: Analyze Dependency Heaviness of R Packages

R: Heaviness from parent packages
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

WA: Weighted averaging (WA) regression and calibration

CRAN

rioja: Analysis of Quaternary Science Data

R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

WA: Weighted averaging (WA) regression and calibration

GITHUB

nsj3/rioja: Analysis of Quaternary Science Data

R: Weighted averaging (WA) regression and calibration
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

heavy: Robust Estimation Using Heavy-Tailed Distributions

CRAN

heavy: Robust Estimation Using Heavy-Tailed Distributions

Package: heavy
Version: 0.38.196
Title: Robust Estimation Using Heavy-Tailed Distributions

mikejohnson51/geogrids: Create mosaiced geogrids with flexable structure

GITHUB

mikejohnson51/geogrids: Create mosaiced geogrids with flexable structure

Package: geogrids
Title: Create mosaiced geogrids with flexable structure
Version: 0.0.1

geogrid: Turn Geospatial Polygons into Regular or Hexagonal Grids

CRAN

geogrid: Turn Geospatial Polygons into Regular or Hexagonal Grids

Package: geogrid
Title: Turn Geospatial Polygons into Regular or Hexagonal Grids
Version: 0.1.2

R/geogrid-package.R
man/geogrid-package.Rd

geogrid: Plots a grid

CRAN

geo: Draw and Annotate Maps, Especially Charts of the North Atlantic

Usage
geogrid(lat, lon = 0, col = 1, type = "l", lwd = 0, lty = 0,
pch = "+", nx = 5)

WA: While-Alive Loss Rate for Recurrent Event in the Presence of Death

CRAN

WA: While-Alive Loss Rate for Recurrent Event in the Presence of Death

Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of

geogrid-package: geogrid: Turn Geospatial Polygons into Regular or Hexagonal...

CRAN

geogrid: Turn Geospatial Polygons into Regular or Hexagonal Grids

R: geogrid: Turn Geospatial Polygons into Regular or Hexagonal...
const macros = { "\\R": "\\textsf{R}", "\\code

geogrid: Plots a grid

RFORGE

geo: Draw and Annotate Maps, Especially Charts of the North Atlantic

Usage
geogrid(lat, lon = 0, col = 1, type = "l", lwd = 0, lty = 0, pch = "+",
nx = 5)

SulawesiBarat: Food Prices in Sulawesi Barat

CRAN

ifpd: Indonesia Food Prices Data

R: Food Prices in Sulawesi Barat
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

WA: SpatialPolygonsDataFrame for the state of Washington, USA

GITHUB

tmcd82070/SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

heaviness: Weights Judging Data

CRAN

eba: Elimination-by-Aspects Models

were aggregated across subjects for the
two within-pair presentation orders.
Usage

wa: Weighted averaging transfer functions

CRAN

analogue: Analogue and Weighted Averaging Methods for Palaeoecology

and classicial
deshrinking are supported.
Usage

WA: SpatialPolygonsDataFrame for the state of Washington, USA

GITHUB

semmons1/TEST-SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

WA: SpatialPolygonsDataFrame for the state of Washington, USA

CRAN

SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

wa: Extracts the weighted averages of a CCA solution

GITHUB

villardon/MultBiplotR: Multivariate Analysis Using Biplots in R

solution
Description
Extracts the weighted averages of a CCA solution

WA: statistic of the Watson goodness-of-fit test for the gamma

CRAN

gofgamma: Goodness-of-Fit Tests for the Gamma Distribution

, i.e. a bootstrap procedure is implemented to perform the test, see crit.values.
Usage
WA(data, k_estimator)

wa: Extracts the weighted averages of a CCA solution

CRAN

MultBiplotR: Multivariate Analysis Using Biplots in R

of a CCA solution
Description
Extracts the weighted averages of a CCA solution

dbca-wa/turtleviewer: WA Turtle Data Viewer

GITHUB

dbca-wa/turtleviewer: WA Turtle Data Viewer

Package: turtleviewer
Title: WA Turtle Data Viewer
Version: 0.2.0.20200102