aibot: 创建查询机器人

GITHUB

takewiki/tsai: takewiki solution for AI

R: 创建查询机器人
aibotR Documentation
创建查询机器人

aibot_env: 增加机器人查询测试env

GITHUB

takewiki/tsai: takewiki solution for AI

R: 增加机器人查询测试env
aibot_envR Documentation
增加机器人查询测试env

experiments/20180409_序列生成机制分析.Rmd:

GITHUB

ahorawzy/TFTSA: Traffic Flow Time Series Analysis

研究分析。
相比第一部分交通流聚类，第二部分我看的文章较少，对于怎么做还不甚清楚。相比第一部分，第二部分所处理数据的工作量没有那么大，但难在思路和方法的创新上，并且要考虑到与第一部分结合。
今天的实验主要是3.4节交通流序列生成机制分析

nse_subScramble: 测试取子集后随机排序

GITHUB

takewiki/tsdo: data objects in takewiki solutions

R: 测试取子集后随机排序
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

get_fit: 重复随机试验计算最优参数

GITHUB

catlain/LTV:

R: 重复随机试验计算最优参数
get_fitR Documentation
重复随机试验计算最优参数

mtrl: 物料处理的主表

GITHUB

takewiki/kdcmtrlpkg:

R: 物料处理的主表
mtrlR Documentation
物料处理的主表

experiments/20171219_10月1日交通流随机森林建模.Rmd:

GITHUB

ahorawzy/TFTSA: Traffic Flow Time Series Analysis

title: "20171219_10月1日交通流随机森林建模"
author: "王致远"
date: "2017年12月19日"

get_ring_retain: 随机获得新用户的环比系数

GITHUB

catlain/LTV:

R: 随机获得新用户的环比系数
get_ring_retainR Documentation
随机获得新用户的环比系数

experiments/20180731_模拟收费数据.Rmd:

GITHUB

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

(lubridate)
library(magrittr)
今天的实验主要是利用昨天下午建好的10个点的小路网，模拟出收费数据，计算交通流。即在小路网上打通1,2,3三步。

dm_chartNo_deleteDB: 按主图号删除数据库

GITHUB

takewiki/lcrdspkg: package for LC RDS project

R: 按主图号删除数据库
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

tg: tg "to grob" helper function

GITHUB

almartin82/mapvizieR: Visualization and Data Analysis tools for NWEA MAP student data

R: tg "to grob" helper function
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function

mo_testData_keys: 测试数据集的主键

GITHUB

takewiki/kdcr: kdc in R

R: 测试数据集的主键
mo_testData_keysR Documentation
测试数据集的主键

mtrl_main: 处理物料主表数据

GITHUB

takewiki/kdcmtrlpkg:

R: 处理物料主表数据
mtrl_mainR Documentation
处理物料主表数据

w0: Simulated w0 data used in Murray et al. (2013)

CRAN

MonoPoly: Functions to Fit Monotone Polynomials

R: Simulated w0 data used in Murray et al. (2013)
w0R Documentation
Simulated w0 data used in Murray et al. (2013

com: com

GITHUB

jfq3/QsNullModels: My null model functions

R: com
comR Documentation
com

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

COM: Full access to client COM invocation

GITHUB

omegahat/RDCOMClient: R-DCOM client

R: Full access to client COM invocation
.COMR Documentation
Full access to client COM invocation

W0: Matrix indicating connections between the observed variables

BIOC

ASGSCA: Association Studies for multiple SNPs and multiple traits using Generalized Structured Equation Models

to estimate the weight coefficients of the model.
Usage
data(W0)

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

vp: Variance Partitioning with Moran Spectral Randomization

CRAN

spfilteR: Semiparametric Spatial Filtering with Eigenvectors in (Generalized) Linear Models

of determination adjusted for spurious correlations.
Usage
vp(y, x = NULL, evecs = NULL, msr = 100)