40: Post-bomb atmospheric 14C fraction

RFORGE
SoilR: Models of Soil Organic Matter Decomposition

R: Post-bomb atmospheric 14C fraction
C14Atm_NHR Documentation
Post-bomb

erebus.40: Image of Erebus Volcano, Antarctica

CRAN
imagefx: Extract Features from Images

the image has been compressed significantly to reduce the memory size.
Usage
data("erebus.40")

WA: Weighted averaging (WA) regression and calibration

CRAN
rioja: Analysis of Quaternary Science Data

assemblages using weighted averaging (WA) regression and calibration.
Usage
WA(y, x, mono=FALSE, tolDW = FALSE, use.N2=TRUE

WA: Weighted averaging (WA) regression and calibration

GITHUB
nsj3/rioja: Analysis of Quaternary Science Data

assemblages using weighted averaging (WA) regression and calibration.
Usage
WA(y, x, mono=FALSE, tolDW = FALSE, use.N2=TRUE

rescaler-40: Rescaler

CRAN
reshape: Flexibly Reshape Data

rescaler(x, type="sd", ...)
Arguments
x

40-generate.MixSim: Generate MixSim Examples for Testing

GITHUB
snoweye/pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Generate MixSim Examples for Testing
const macros = { "\\R": "\\textsf{R

40-generate.basic: Generate Examples for Testing

CRAN
pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Generate Examples for Testing
generate.basicR Documentation
Generate

40-generate.MixSim: Generate MixSim Examples for Testing

CRAN
pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Generate MixSim Examples for Testing
generate.MixSimR Documentation

40-generate.basic: Generate Examples for Testing

GITHUB
snoweye/pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

R: Generate Examples for Testing
const macros = { "\\R": "\\textsf{R

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

Florian-40/mypkgr: My 1st package

GITHUB
Florian-40/mypkgr: My 1st package

/Florian-40/mypkgr,
https://florian-40.github.io/mypkgr/
BugReports: https://github.com/Florian-40/mypkgr/issues

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")

X: X

GITHUB
arthans/SpectralClustering: Spectral Clustering

R: X
XR Documentation
X

X: X

RFORGE
miRtest: Combined miRNA- and mRNA-Testing

R: X
XR Documentation
X

inst/charts/40.R:

GITHUB
NicolasJBM/writer: Functions and interfaces to support academic writing with R

() %>%
add_trace(
x = ~gdpPercap,

WA: statistic of the Watson goodness-of-fit test for the gamma

CRAN
gofgamma: Goodness-of-Fit Tests for the Gamma Distribution

transform". Communications in Statistics - Theory and Methods, 41(9): 1543-1556. DOI
Examples
X=stats::rgamma(20,3,6)

R/40-priority_queue-apply.R:

CRAN
Immutables: Fast and Functional Data Structures

fapply.priority_queue <- function(X, FUN, ..., preserve_custom_monoids = TRUE) {
if(!is.function(FUN)) {
stop("`FUN` must