fiber: fiber

GITHUB

kim3-sudo/expdesigndata: Datasets For Experimental Design

R: fiber
fiberR Documentation
fiber

fiber: Fiber data

CRAN

emmeans: Estimated Marginal Means, aka Least-Squares Means

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

fiber: Fiber Strength Dataset

CRAN

HoRM: Supplemental Functions and Datasets for "Handbook of Regression Methods"

R: Fiber Strength Dataset
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

fiber: Fiber Strength Dataset

GITHUB

dsy109/HoRM: Supplemental Functions and Datasets for "Handbook of Regression Methods"

R: Fiber Strength Dataset
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

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

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

count-fiber: Count the elements of a fiber Ax = b

GITHUB

dkahle/algstat: Algebraic Statistics

R: Count the elements of a fiber Ax = b
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

Fibers: Tensile strengths

CRAN

EstimationTools: Maximum Likelihood Estimation for Probability Functions from Data Sets

) of 69 specimens of carbon fiber tested under tension
at gauge lengths of 20 mm.
Usage

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: 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