warna: warna

GITHUB
ilyamaclean/climvars: Functions for calculating biologically meaningful climate variables

R: warna
warnaR Documentation
warna

acp: Autoregressive Conditional Poisson (ACP) Regression

CRAN
acp: Autoregressive Conditional Poisson

R: Autoregressive Conditional Poisson (ACP) Regression
acpR Documentation
Autoregressive Conditional Poisson (ACP

acp: Autoregressive Conditional Poisson (ACP) Regression

GITHUB
mpiktas/acp: Autoregressive Conditional Poisson

R: Autoregressive Conditional Poisson (ACP) Regression
acpR Documentation
Autoregressive Conditional Poisson (ACP

WA: Weighted averaging (WA) regression and calibration

CRAN
rioja: Analysis of Quaternary Science Data

method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns

WA: Weighted averaging (WA) regression and calibration

GITHUB
nsj3/rioja: Analysis of Quaternary Science Data

method that produces scatter plots of predicted vs observed measurements for the training set.
Value
Function WA returns

modern: Modern refine

CRAN
ggrefine: Publication-Quality 'ggplot2' Themes

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

modern: A data frame of modern and contemporary historical and...

CRAN
despair: Motivational Quotes and Shakespearean Bard–bits for Personal Projects

R: A data frame of modern and contemporary historical and...
const macros = { "\\R": "\\textsf{R}", "\\code

Modern: Agricultural Data gathered in an experimental setting

GITHUB
christianu7/aistats2020smi: Semi-Modular Inference

in an experimental setting
Description
The Modern data were gathered in an experimental setting in which manure level

acp: Adaptive conformal prediction method

CRAN
conformalForecast: Conformal Prediction Methods for Multistep-Ahead Time Series Forecasting

, initial = 1, window = 50)
# ACP with asymmetric nonconformity scores and rolling calibration sets
acpfc <- acp(fc

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

acp: Principal component analysis

CRAN
amap: Another Multidimensional Analysis Package

component analysis
Usage
acp(x,center=TRUE,reduce=TRUE,wI=rep(1,nrow(x)),wV=rep(1,ncol(x)))

acp: Anlisis de componentes principales

GITHUB
jcms2665/ACP:

Description
An<c3><a1>lisis de componentes principales.
Usage

acp: Optimization using an iterative hill-climbing algorithm

GITHUB
matsukik/mrsat: Multiple Response Speed Accuracy Tradeoff

-climbing algorithm
Description
Box-constrained optimization using an iterative hill-climbing algorithm

acp: Autoregressive Conditional Poisson

CRAN
acp: Autoregressive Conditional Poisson

Package: acp
Title: Autoregressive Conditional Poisson
Version: 2.1

avery-kruger/kitchen: Convolutional Kitchen Sinks in R

GITHUB
avery-kruger/kitchen: Convolutional Kitchen Sinks in R

Package: kitchen
Type: Package
Title: Convolutional Kitchen Sinks in R

acp: Add, Commit, and Push

GITHUB
meerapatelmd/glitter: Send Git commands via the R Console

R: Add, Commit, and Push
acpR Documentation
Add, Commit, and Push

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

mod <- wa(SumSST ~., data = ImbrieKipp)
## extract the fitted values
fitted(mod)

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")