warna: warna

GITHUB

ilyamaclean/climvars: Functions for calculating biologically meaningful climate variables

R: warna
warnaR Documentation
warna

peach: uni.kn color Peach.

GITHUB

vidonne/unhcr_theme: Graphical Elements of the University of Konstanz's Corporate Design

R: uni.kn color Peach.
PeachR Documentation
uni.kn color Peach.

peach: Pesticide residue measurements for peaches

CRAN

pesticides: Analysis of single serving and composite pesticide residue measurements

R: Pesticide residue measurements for peaches
peachR Documentation
Pesticide residue measurements for peaches

Peach: uni.kn color Peach

CRAN

unikn: Graphical Elements of the University of Konstanz's Corporate Design

R: uni.kn color Peach
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

WA: Weighted averaging (WA) regression and calibration

CRAN

rioja: Analysis of Quaternary Science Data

method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns

WA: Weighted averaging (WA) regression and calibration

GITHUB

nsj3/rioja: Analysis of Quaternary Science Data

method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns

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)

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)

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

peach: Pareto Enrichment Analysis for Combining Heterogeneous

CRAN

PEACH: Pareto Enrichment Analysis for Combining Heterogeneous Datasets

individual dataset as well as the pareto combined pathway p-values in a data frame.
Usage
peach(

PEACH: Detection of cell separation–induced gene expression through

GITHUB

AshTai/PEACH:

–induced gene expression through a penalized deconvolution approach.
Description
PEACH adopts a deconvolution method

avery-kruger/kitchen: Convolutional Kitchen Sinks in R

GITHUB

avery-kruger/kitchen: Convolutional Kitchen Sinks in R

Package: kitchen
Type: Package
Title: Convolutional Kitchen Sinks in R

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

mod <- wa(SumSST ~., data = ImbrieKipp)
## extract the fitted values
fitted(mod)

WA: SpatialPolygonsDataFrame for the state of Washington, USA

GITHUB

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

of Washington.
Usage
data("WA")

PEACH: Pareto Enrichment Analysis for Combining Heterogeneous Datasets

CRAN

PEACH: Pareto Enrichment Analysis for Combining Heterogeneous Datasets

Package: PEACH
Title: Pareto Enrichment Analysis for Combining Heterogeneous Datasets
Version: 0.1.1

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)