bali: Bali terrorist network

CRAN

hergm: Hierarchical Exponential-Family Random Graph Models

R: Bali terrorist network
baliR Documentation
Bali terrorist network

scanner: scanner

CRAN

envlpaster: Enveloping the Aster Model

R: scanner
scannerR Documentation
scanner

Bali: Food Prices in Bali

CRAN

ifpd: Indonesia Food Prices Data

R: Food Prices in Bali
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

bali: Bali terrorist network

CRAN

bigergm: Fit, Simulate, and Diagnose Hierarchical Exponential-Family Models for Big Networks

R: Bali terrorist network
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

scanner: standard RGB scanners

CRAN

colorSpec: Color Calculations with Emphasis on Spectral Data

R: standard RGB scanners
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

axe-xrf: Axing a xrf.

CRAN

butcher: Model Butcher

R: Axing a xrf.
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

serVis: View and/or share LDAvis in a browser

CRAN

LDAvis: Interactive Visualization of Topic Models

View and/or share LDAvis in a browser.
Usage
serVis(json, out.dir = tempfile(), open.browser = interactive(),

serVis: View and/or share LDAvis in a browser

GITHUB

cpsievert/LDAvis: Interactive Visualization of Topic Models

View and/or share LDAvis in a browser.
Usage
serVis(json, out.dir = tempfile(), open.browser = interactive(),

xrf: eXtreme RuleFit

CRAN

xrf: eXtreme RuleFit

Package: xrf
Title: eXtreme RuleFit
Version: 0.3.1

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

Scanner: Scan the contents of a dataset

CRAN

arrow: Integration to 'Apache' 'Arrow'

A Scanner iterates over a Dataset's fragments and returns data
according to given row filtering and column projection

scanner: Scan List of Text Files

GITHUB

couthcommander/packageDiff: Compare R Package Differences

string
Usage
scanner(files, full.names = FALSE)

Scanner: scans for dependences of a file scan a file for dependences

GITHUB

roverrobot/make: Make utility in R

of a file
scan a file for dependences
Description

xrf: Fit an eXtreme RuleFit model

CRAN

xrf: eXtreme RuleFit

for building an "eXtreme RuleFit" model.
See xrf.formula for preferred entry point
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")