Arena: arena class

GITHUB

Atan1988/rothello:

R: arena class
ArenaR Documentation
arena class

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

PAPE: Estimation of the Population Average Prescription Effect

GITHUB

MichaelLLi/evalITR: Evaluating Individualized Treatment Rules

in Imai and Li (2019).
Usage
PAPE(T, That, Y, budget = NA, centered = TRUE)

PAPE: Estimation of the Population Average Prescription Effect

CRAN

evalITR: Evaluating Individualized Treatment Rules

in Imai and Li (2019).
Usage
PAPE(T, That, Y, budget = NA, centered = TRUE)

PAPE: Estimation of the Population Average Prescription Effect

CRAN

experiment: R Package for Designing and Analyzing Randomized Experiments

in Imai and Li (2019).
Usage
PAPE(T, That, Y, plim = NA)

RAB: real adaboost (Friedman et al

GITHUB

lgatto/MLInterfaces: Uniform interfaces to R machine learning procedures for data in Bioconductor containers

... a demonstration version
Usage
RAB(formula, data, maxiter=200, maxdepth=1)

Arena-class: Structure of the S4 class "Arena"

CRAN

BacArena: Modeling Framework for Cellular Communities in their Environments

R: Structure of the S4 class "Arena"
Arena-classR Documentation
Structure of the S4 class "Arena"

RAB: Compute the relative absolute bias of multiple estimators

CRAN

SimDesign: Structure for Organizing Monte Carlo Simulation Designs

estimators.
Usage
RAB(x, percent = FALSE, unname = FALSE)

RAB: real adaboost (Friedman et al

BIOC

MLInterfaces: Uniform interfaces to R machine learning procedures for data in Bioconductor containers

... a demonstration version
Usage
RAB(formula, data, maxiter=200, maxdepth=1)

Arena-class: Structure of the S4 class "Arena"

GITHUB

euba/BacArena: Modeling Framework for Cellular Communities in their Environments

R: Structure of the S4 class "Arena"
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

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

Arena-constructor: Constructor of the S4 class 'Arena-class'

CRAN

BacArena: Modeling Framework for Cellular Communities in their Environments

R: Constructor of the S4 class 'Arena-class'
Arena-constructorR Documentation
Constructor of the S4 class Arena

Arena-constructor: Constructor of the S4 class 'Arena-class'

GITHUB

euba/BacArena: Modeling Framework for Cellular Communities in their Environments

R: Constructor of the S4 class 'Arena-class'
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")

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: 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: SpatialPolygonsDataFrame for the state of Washington, USA

CRAN

SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

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)