warna: warna

GITHUB

ilyamaclean/climvars: Functions for calculating biologically meaningful climate variables

R: warna
warnaR Documentation
warna

pvc: Production of PVC by operator and resin railcar

CRAN

faraway: Datasets and Functions for Books by Julian Faraway

R: Production of PVC by operator and resin railcar
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

WA: Weighted averaging (WA) regression and calibration

CRAN

rioja: Analysis of Quaternary Science Data

^2 + v2^2.
Function crossval also returns an object of class WA and adds the following named elements:
predicted

WA: Weighted averaging (WA) regression and calibration

GITHUB

nsj3/rioja: Analysis of Quaternary Science Data

^2 + v2^2.
Function crossval also returns an object of class WA and adds the following named elements:
predicted

flatness: flatness: a package to assess the flatness of (rank)...

CRAN

flatness: Indices and Tests for Assessing the Flatness of (Rank) Histograms

R: flatness: a package to assess the flatness of (rank)...
flatnessR Documentation
flatness: a package to assess

PVC: A Modified Algorithm for Principal Volatility Component

CRAN

tsBSS: Blind Source Separation and Supervised Dimension Reduction for Time Series

Volatility Component Estimator
Description
PVC (Principal Volatility Component) estimator for the blind source

flat: Flat sequences

CRAN

INQC: Quality Control of Climatological Daily Time Series

R: Flat sequences
flatR Documentation
Flat sequences

flat: Flat sequences

GITHUB

INDECIS-Project/INQC: Quality Control of Climatological Daily Time Series

R: Flat sequences
flatR Documentation
Flat sequences

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

flat: Serialize Objects to Flat Strings

CRAN

transltr: Support Many Languages in R

R: Serialize Objects to Flat Strings
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

Flat: A convenience function for generating a flat prior.

CRAN

prefeR: R Package for Pairwise Preference Elicitation

R: A convenience function for generating a flat prior.
FlatR Documentation
A convenience function for generating

Flat: A convenience function for generating a flat prior.

GITHUB

jlepird/prefeR: R Package for Pairwise Preference Elicitation

R: A convenience function for generating a flat prior.
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

Flat: A convenience function for generating a flat prior.

GITHUB

jlepird/BayesPref: R Package for Pairwise Preference Elicitation

R: A convenience function for generating a flat prior.
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

WA: SpatialPolygonsDataFrame for the state of Washington, USA

GITHUB

tmcd82070/SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

flatness: Indices and Tests for Assessing the Flatness of (Rank) Histograms

CRAN

flatness: Indices and Tests for Assessing the Flatness of (Rank) Histograms

Package: flatness
Type: Package
Title: Indices and Tests for Assessing the Flatness of (Rank)

wa: Weighted averaging transfer functions

CRAN

analogue: Analogue and Weighted Averaging Methods for Palaeoecology

## tolerance DW
mod3 <- wa(SumSST ~ ., data = ImbrieKipp, tol.dw = TRUE,
min.tol = 2, small.tol = "mean

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)