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

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

WA: SpatialPolygonsDataFrame for the state of Washington, USA

GITHUB
tmcd82070/SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

WA: SpatialPolygonsDataFrame for the state of Washington, USA

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

of Washington.
Usage
data("WA")

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

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

50: pass through constructor

RFORGE
SoilR: Models of Soil Organic Matter Decomposition

R: pass through constructor
DecompOp_method__DecompOpR Documentation
pass

dbca-wa/wastdr: WA Sea Turtle Database 'WAStD' API Wrapper

GITHUB
dbca-wa/wastdr: WA Sea Turtle Database 'WAStD' API Wrapper

Type: Package
Package: wastdr
Title: WA Sea Turtle Database 'WAStD' API Wrapper

eat.unicorns.50: A student strategy

GITHUB
MartinKies/USLR: Reinforcement Learning with R

R: A student strategy
eat.unicorns.50R Documentation
A student strategy

50-mb.print: Print Results of Model-Based Clustering

CRAN
pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Print Results of Model-Based Clustering
mb.printR Documentation
Print

50-indep.logL: Independent Function for Log Likelihood

CRAN
pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Independent Function for Log Likelihood
Independent logLR Documentation

50-update.class: Update CLASS.spmd Based on the Final Iteration

GITHUB
snoweye/pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Update CLASS.spmd Based on the Final Iteration
const macros = { "\\R

50-indep.logL: Independent Function for Log Likelihood

GITHUB
snoweye/pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Independent Function for Log Likelihood
const macros = { "\\R": "\\textsf

updatelist-50: Update list

CRAN
reshape: Flexibly Reshape Data

R: Update list
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

50-update.class: Update CLASS.spmd Based on the Final Iteration

CRAN
pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Update CLASS.spmd Based on the Final Iteration
Update Class of EM