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

gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

CRAN
gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

Package: gRc
Version: 0.5.1
Title: Inference in Graphical Gaussian Models with Edge and Vertex

demo/gRc-JSS.R
man/grc-summary.Rd

grc-summary: The package 'gRc': summary information

CRAN
gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

R: The package 'gRc': summary information
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

grc-summary: The package 'gRc': summary information

GITHUB
hojsgaard/gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

R: The package 'gRc': summary information
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

grc: Greece

GITHUB
jcpernias/RPIAAC: Datasets from PIAAC

for the International
Assesment of Adult competencies.
Usage

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

gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

RFORGE
gRc: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries

Package: gRc
Version: 0.4-1
Title: Inference in Graphical Gaussian Models with Edge and Vertex

gRc-Ex.R
demo/gRc-JSS.R

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

grc: Row-Column Interaction Models including Goodman's RC

CRAN
VGAM: Vector Generalized Linear and Additive Models

association model (GRC) to a matrix of counts,
and more generally, row-column interaction models (RCIMs).
RCIMs allow

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")

GRC: Greece

GITHUB
covid19datahub/COVID19dev: COVID-19 Data Hub

, macros }); }
return;
GRCR Documentation