motor: Motor Vibration Data

CRAN

MPV: Data Sets from Montgomery, Peck and Vining

R: Motor Vibration Data
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

motors: Diagnostic of electrical induction motors

CRAN

isoboost: Isotonic Boosting Classification Rules

R: Diagnostic of electrical induction motors
motorsR Documentation
Diagnostic of electrical induction motors

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

motor: Multivariate time series dataset on the temperature

CRAN

dbnR: Dynamic Bayesian Network Learning and Inference

series dataset on the temperature of an electric motor
Description
Data from several sensors on an electric motor

motor: Multivariate time series dataset on the temperature

GITHUB

dkesada/dbnR: Dynamic Bayesian Network Learning and Inference

series dataset on the temperature of an electric motor
Description
Data from several sensors on an electric motor

motor: Multivariate time series dataset on the temperature

GITHUB

dkesada/rdbn: Dynamic Bayesian Network Learning and Inference

series dataset on the temperature of an electric motor
Description
Data from several sensors on an electric motor

motors: Accelerated Life Testing of Motorettes

CRAN

MASS: Support Functions and Datasets for Venables and Ripley's MASS

Description
The motors data frame has 40 rows and 3 columns. It describes an
accelerated life test at each of four

motor: Data from a Simulated Motorcycle Accident

CRAN

boot: Bootstrap Functions (Originally by Angelo Canty for S)

Accident
Description
The motor data frame has 94 rows and 4 columns. The rows are

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")

Motor: Phase differences in hand flexion-extension movements

GITHUB

joliencremers/bpnreg: Bayesian Projected Normal Regression Models for Circular Data

human motor resonance.
Usage
Motor

Motor: Phase differences in hand flexion-extension movements

CRAN

bpnreg: Bayesian Projected Normal Regression Models for Circular Data

human motor resonance.
Usage
Motor

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

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