grass: grass

GITHUB

lschen-stat/SNPath: Algorithms for pathway analysis using SNP data

R: grass
grass R Documentation
grass

Grass: The effects of fertilizers on coastal Bermuda grass

CRAN

glmtoolbox: Set of Tools to Data Analysis using Generalized Linear Models

R: The effects of fertilizers on coastal Bermuda grass
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

grass: Wet grass example

GITHUB

DataSciBurgoon/gRain: Graphical Independence Networks

R: Wet grass example
grassR Documentation
Wet grass example

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

Grass: Yields from Nitrogen nutrition of grass species

RFORGE

candisc: Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis

R: Yields from Nitrogen nutrition of grass species
GrassR Documentation
Yields from Nitrogen nutrition of grass

Grass: Yields from Nitrogen nutrition of grass species

CRAN

candisc: Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis

R: Yields from Nitrogen nutrition of grass species
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

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

KalimantanSelatan: Food Prices in Kalimantan Selatan

CRAN

ifpd: Indonesia Food Prices Data

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

grass: Data for Friedman test

CRAN

agricolae: Statistical Procedures for Agricultural Research

identical
areas in his yard and to plant four different types of grasses, one in each area.
Usage

grasses: Water potential example dataset

CRAN

seedr: Hydro and Thermal Time Seed Germination Models in R

This is a dataset containing information from a water potential experiment
with grass seeds. It is used to give examples

WA: SpatialPolygonsDataFrame for the state of Washington, USA

GITHUB

tmcd82070/SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

grass: Data for Friedman test

GITHUB

myaseen208/agricolae: Statistical Procedures for Agricultural Research

identical
areas in his yard and to plant four different types of grasses, one in each
area.

grass: Agricultural factorial design

CRAN

asbio: A Collection of Statistical Tools for Biologists

grass varieties. The seed growing methods were applied to seed from each grass variety.
Six pots were planted

grasses: Water potential example dataset

GITHUB

efernandezpascual/seedr: Hydro and Thermal Time Seed Germination Models in R

This is a dataset containing information from a water potential experiment
with grass seeds. It is used to give examples

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)