GitHub - facebook/prophet: Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
R 3.0.0 is released! (what’s new, and how to upgrade) | R-bloggers
[This article was first published on R-statistics blog » RR-statistics blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. A few hours ago Peter Dalgaard (of R Core Team) announced the release of R 3.0.0! Bellow you can read the changes in this release
littler: a scripting front-end for GNU R
littler: A scripting and command-line front-end for GNU R So What Is It For? #!/usr/bin/env r ## for use in scripts other input | r ## for use in pipes r somefile.R ## for running files r -e 'expr' ## for evaluating expressions r --help ## to show a quick synopsis Examples? Plenty. See the examples vignette for a full set of introductory examples. Also see the examples/ directory for a full 28 exa
The R programming language for programmers coming from other programming languages
R programming for those coming from other languages Introduction Assignment and underscore Variable name gotchas Vectors Sequences Types Boolean operators Lists Matrices Missing values and NaNs Comments Functions Scope Misc. Other resources Ukrainian translation Other languages: Introduction I have written software professionally in perhaps a dozen programming languages, and the hardest language f
A Roadmap for Rich Scientific Data Structures in Python | Quant Pythonista
Discussion thread on Hacker News So, this post is a bit of a brain dump on rich data structures in Python and what needs to happen in the very near future. I care about them for statistical computing (I want to build a statistical computing environment that trounces R) and financial data analysis (all evidence leads me to believe that Python is the best all-around tool for the finance space). Othe
Calling R lovers and bloggers – to work together on "The R Programming wikibook" | R-statistics blog
Engineering Data Analysis (with R and ggplot2) – a Google Tech Talk given by Hadley Wickham | R-statistics blog
It appears that just days ago, Google Tech Talk released a new, one hour long, video of a presentation (from June 6, 2011) made by one of R’s community more influential contributors, Hadley Wickham. This seems to be one of the better talks to send a programmer friend who is interested in getting into R. Talk abstractData analysis, the process of converting data into knowledge, insight and understa
Rによる計算機統計学 | Ohmsha
序 文 訳者前書き 第1章 R 環境と計算機統計学 第2章 確率と統計学の概説 第3章 確率変数の発生方法 第4章 多変量データの視覚化 第5章 モンテカルロ積分と分散減少法 第6章 推論におけるモンテカルロ法 第7章 ブートストラップ法とジャックナイフ法 第8章 並べ替え検定 第9章 マルコフ連鎖モンテカルロ法 第10章 確率密度推定 第11章 R の数値解析 付録A 表記法 付録B データフレームと配列を用いた操作 参考文献 索 引 序 文 訳者前書き 第1章 R 環境と計算機統計学 1.1 計算機統計学と統計コンピューティング 1.2 R 環境 1.3 R を始めるには 1.4 R のオンラインヘルプシステムの利用 1.5 関数 1.6 配列、データフレーム、リスト 1.7 R のワークスペースとファイル 1.8 スクリプトの利用 1.9 パッケージの利用 1.10 グラフィック
How to Make Bubble Charts
Ever since Hans Rosling presented a motion chart to tell his story of the wealth and health of nations, there has been an affinity for proportional bubbles on an x-y axis. This tutorial is for the static version of the motion chart: the bubble chart. A bubble chart can also just be straight up proportionally sized bubbles, but here we’re going to cover how to create the variety that is like a scat
実践！ Rで学ぶ統計解析の基礎 － ＠IT
Rは統計解析のブッシュナイフだ 実践！ Rで学ぶ統計解析の基礎（1） オープンソースの統計処理言語・環境の「R」を使って実践的な統計解析のテクニックとリテラシーを習得しよう！
ggplot2についてちょっと勉強した(1) - もうカツ丼はいいよな
ggplot2について ggplot2 要するにRでちょっとカッコイイグラフが簡単に作れるアレ。 リファレンスマニュアルを読んだのでノートを書く。 とりあえずhttp://had.co.nz/ggplot2/geom_abline.htmlを読んだ。点の打ち方と線の引き方。 まあでもぶっちゃけhttp://had.co.nz/ggplot2/geom_abline.htmlを省略しつつ訳しただけのようなものなのであまり面白くn*1(ry ノート 使われるデータセットについて 自動車のデータ ?mtcars 1974年のMotor Trend US紙から抽出 燃費ほか10の項目、32車種分のデータ mpg: 燃費(Miles/(US)gallon) cyl: シリンダー数 disp:排気量(立方インチ？) hp: 馬力 wt: 重量(ポンド/1000) qsec:1/4マイルのタイム vs:
R Graphical Manual
32,329 images, 2,614 packages, 50,851 functions, 8,814 datasets. Last data update: 2010-10-19 (R version 2.11.1)
rpy2
The rpy2 site has moved to https://rpy2.bitbucket.io. You will be redirected in 15 s econds. About rpy2 is an interface to R running embedded in a Python process. The project is mature, stable, and widely used. Source and installation Released source packages are available on PyPi. Installing should be as easy as pip install rpy2 The source code is also in a public repository on bitbucket. Documen
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
https://rstudio.github.io/keras/
Amazon.co.jp: 「R」でおもしろくなるファイナンスの統計学 (知識ゼロでもわかる統計学): 横内大介: 本
Sean Davis - Accessing Public Data using R and Bioconductor
RStudio
google-motion-charts-with-r - Using the Google Visualisation API with R - Google Project Hosting
http://www.red-r.org/
SHO FUJIHARA'S PAGE - R