aws: AWS downloader

GITHUB

RajLabMSSM/downloadR: echoverse module: Single- and multi-threaded downloading functions

R: AWS downloader
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML

experiments/20180820_黑龙江真实路网实验3.Rmd:

GITHUB

ahorawzy/HVS: This package is designed for Highway Virtual Traffic Survey Station project.

title: "20180820_黑龙江真实路网实验3"
author: "wzy"
date: "2018年8月20日"

aws: AWS for local constant models on a grid

GITHUB

neuroconductor-releases/aws: Adaptive Weights Smoothing

R: AWS for local constant models on a grid
awsR Documentation
AWS for local constant models on a grid

aws: AWS for local constant models on a grid

GITHUB

WIAS-BERLIN/aws: Adaptive Weights Smoothing

R: AWS for local constant models on a grid
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

aws: AWS for local constant models on a grid

CRAN

aws: Adaptive Weights Smoothing

R: AWS for local constant models on a grid
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

aws: AWS for local constant models on a grid

GITHUB

neuroconductor/aws: Adaptive Weights Smoothing

R: AWS for local constant models on a grid
awsR Documentation
AWS for local constant models on a grid

awes: awes - Adaptively Weighted Ensembles via Stacking

GITHUB

reichlab/adaptively-weighted-ensemble: Adaptively Weighted Ensembles via Stacking

R: awes - Adaptively Weighted Ensembles via Stacking
awesR Documentation
awes - Adaptively Weighted Ensembles via

experiments/20180801_DT加速实验.Rmd:

GITHUB

ahorawzy/HVS: This package is designed for Highway Virtual Traffic Survey Station project.

title: "20180801_DT加速实验"
author: "wzy"
date: "2018年8月1日"

experiments/20180809_黑龙江真实路网实验.Rmd:

GITHUB

ahorawzy/HVS: This package is designed for Highway Virtual Traffic Survey Station project.

title: "20180809_黑龙江真实路网实验"
author: "wzy"
date: "2018年8月9日"

aws-class: Class '"aws"'

GITHUB

neuroconductor/aws: Adaptive Weights Smoothing

R: Class '"aws"'
aws-classR Documentation
Class "aws"

aws: Adaptive Weights Smoothing

CRAN

aws: Adaptive Weights Smoothing

Package: aws
Version: 2.5-6
Date: 2024-09-29

inst/doc/aws-Example.pdf
inst/doc/aws-Example.R

f_weibo_app_followtags: 文本向量词云

GITHUB

yibochen/weiBor: fetch and analyse weibo data

R: 文本向量词云
f_weibo_app_followtagsR Documentation
文本向量词云

experiments/20180813_黑龙江真实路网实验2.Rmd:

GITHUB

ahorawzy/HVS: This package is designed for Highway Virtual Traffic Survey Station project.

title: "20180813_黑龙江真实路网实验2"
author: "wzy"
date: "2018年8月13日"

aws-class: Class '"aws"'

GITHUB

neuroconductor-releases/aws: Adaptive Weights Smoothing

R: Class '"aws"'
aws-classR Documentation
Class "aws"

aws-class: Class '"aws"'

CRAN

aws: Adaptive Weights Smoothing

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

aws-class: Class '"aws"'

GITHUB

WIAS-BERLIN/aws: Adaptive Weights Smoothing

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

get_prediction_daily: 使用已有系数拟合预测DAU并计算差异

GITHUB

catlain/LTV:

R: 使用已有系数拟合预测DAU并计算差异
get_prediction_dailyR Documentation
使用已有系数拟合预测DAU并计算差异

shinyElement-class: 定义shinyElement的虚拟类

GITHUB

takewiki/tsShiny:

R: 定义shinyElement的虚拟类
shinyElement-classR Documentation
定义shinyElement的虚拟类

AW: Collection of Free Induction Decay of Urine Spectra

CRAN

musicNMR: Conversion of Nuclear Magnetic Resonance Spectra in Audio Files

) from eight urine samples. All urine were collected from the donor "AW". The urine are divided in two group; in each group

leeper/r-aws: A basic wrapper to the AWS Java

GITHUB

leeper/r-aws: A basic wrapper to the AWS Java

Package: r-AWS
Type: Package
Title: A basic wrapper to the AWS Java

inst/aws-java-sdk/currentVersion.txt
inst/aws-java-sdk/lib/aws-java-sdk-1.1.0-javadoc.jar