Rail: Evaluation of Stress in Railway Rails

GITHUB
bbolker/nlme: Linear and Nonlinear Mixed Effects Models

R: Evaluation of Stress in Railway Rails
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

Rail: Evaluation of Stress in Railway Rails

CRAN
nlme: Linear and Nonlinear Mixed Effects Models

R: Evaluation of Stress in Railway Rails
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

Rail: Evaluation of Stress in Railway Rails

RFORGE
MEMSS: Data sets from Mixed-effects Models in S

R: Evaluation of Stress in Railway Rails
RailR Documentation
Evaluation of Stress in Railway Rails

Rail: Evaluation of Stress in Railway Rails

CRAN
MEMSS: Data Sets from Mixed-Effects Models in S

R: Evaluation of Stress in Railway Rails
RailR Documentation
Evaluation of Stress in Railway Rails

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

rails: Download a national rails shapefile into R

CRAN
tigris: Load Census TIGER/Line Shapefiles

R: Download a national rails shapefile into R
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

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)

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)

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: 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)

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