mold: Mold data for modeling

GITHUB

DavisVaughan/hardhat: Construct Modeling Packages

R: Mold data for modeling
moldR Documentation
Mold data for modeling

mold: Mold data for modeling

CRAN

hardhat: Construct Modeling Packages

R: Mold data for modeling
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

kota: Indonesia city and regency data

GITHUB

rasyidstat/nusantr: We R Nusantara

"Kota" and "Kabupaten"
typeType of geolevel2, "Kota" or "Kabupaten"
Source

ma: MA

CRAN

linea: Linear Regression Interface

R: MA
maR Documentation
MA

mas: mas

GITHUB

USDA-ARS-GBRU/crossword: Breeding program similation sotware

R: mas
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

ma: ma

GITHUB

SVA-SE/svamap: Package to produce data summaries for the web

R: ma
maR Documentation
ma

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)

Ma: Moving average (MA) model

CRAN

gsignal: Signal Processing

R: Moving average (MA) model
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

ma: Prepare data for MA plot

GITHUB

LUMC/dgeAnalysis: dgeAnalysis

R: Prepare data for MA plot
maR Documentation
Prepare data for MA plot

ma: Prepare data for MA plot

GITHUB

LUMC/DGE_analysis: dgeAnalysis

R: Prepare data for MA plot
maR Documentation
Prepare data for MA plot

MA: Generates the MA plot

GITHUB

dianalow/nMyo: nMyo

R: Generates the MA plot
MAR Documentation
Generates the MA plot

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)

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

MA: Create an Moving Average Q [MA(Q)] Process

CRAN

simts: Time Series Analysis Tools

R: Create an Moving Average Q [MA(Q)] Process
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt

run-mold: 'mold()' according to a blueprint

CRAN

hardhat: Construct Modeling Packages

R: 'mold()' according to a blueprint
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

Ma: Create a moving average (MA) model

RFORGE

signal: Signal Processing

R: Create a moving average (MA) model
MaR Documentation
Create a moving average (MA) model

Ma: Create a moving average (MA) model

CRAN

signal: Signal Processing

R: Create a moving average (MA) model
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function