WA: Weighted averaging (WA) regression and calibration

CRAN

rioja: Analysis of Quaternary Science Data

to be modelled or an object of class WA.
newdata
new biological data to be predicted.

WA: Weighted averaging (WA) regression and calibration

GITHUB

nsj3/rioja: Analysis of Quaternary Science Data

to be modelled or an object of class WA.
newdata
new biological data to be predicted.

kota: Indonesia city and regency data

GITHUB

rasyidstat/nusantr: We R Nusantara

of Indonesia cities and regencies with the ID.
Usage
kota

dana: Impact of Outliers - Target Contact

GITHUB

gitrman/itns: Datasets from the book Introduction to the New Statistics

dana
Format
A data frame with 38 rows and 2 variables:

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: Weighted averaging transfer functions

CRAN

analogue: Analogue and Weighted Averaging Methods for Palaeoecology

,..., model = FALSE)
## S3 method for class 'wa'
fitted(object, ...)

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: 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

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

LXQin/DANA: Data-driven Normalization Assessment for miRNA-Seq Data

GITHUB

LXQin/DANA: Data-driven Normalization Assessment for miRNA-Seq Data

Package: DANA
Type: Package
Title: Data-driven Normalization Assessment for miRNA-Seq Data

Model: Model

GITHUB

qhu75/fhiRclient: SMART FHIR Client

R: Model
ModelR Documentation
Model

Model: Model

GITHUB

rpc5102/rlocker: Learning Locker for Shiny

R: Model
ModelR Documentation
Model

Model: Model

GITHUB

EducationShinyAppTeam/rLocker: Learning Locker for Shiny

R: Model
ModelR Documentation
Model

models: Models

GITHUB

Bishop-Laboratory/RLHub: An ExperimentHub package for accessing processed RLSuite data sets

R: Models
fft_modelR Documentation
Models

models: models

CRAN

bayesnec: A Bayesian No-Effect- Concentration (NEC) Algorithm

R: models
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {