A bag of tweets / Apr 2012


Here is the latest bag of tweets*, which covers April 2012.

(*) These are interesting news that I found on Twitter and that I archive periodically.

  • PairachChamp: How to avoid annoying a referee http://t.co/QBKnTdo3 via @robjhyndman (27 Apr)
  • PairachChamp: Using #Rstats to teach #Econometrics by @robjhyndman http://t.co/oE2cVLc6 @R4Econ (27 Apr)
  • revodavid: Can it be done in R? There's a package for that! Great list of #rstats equivalents to #SAS/#SPSS from @BobMuenchen: http://t.co/ZJaaOE4q (27 Apr)
  • bigdata: More from #RLang paper, see p.18: R is slow/inefficient ... need full rewrite of the implementation http://t.co/u77cMzy8 cc @piccolbo (27 Apr)
  • swannodette: This is a good read, Clojure's IFn vs. Python's call http://t.co/obqvOrtS (27 Apr)
  • Periscopic: Data and visualization blogs worth following http://t.co/IQtF8Olf (27 Apr)
  • beckerhopper: Getting started with R? Check out our new book "Getting Started with R" http://t.co/hGXv4Zpf -one to read before all the others. #rstats (27 Apr)
  • StackTeX: "Inspirational" quote at start of chapter http://t.co/q3Av5JdT #chapters (26 Apr)
  • StackTeX: Great answer: Entire course with beamer http://t.co/JYmWf33x #beamer (25 apr)
  • kshameer: A review of a multifactorial probability-based model for classification of BRCA1 and BRCA2 variants of uncertain... http://t.co/dyaxAeRd (24 Apr)
  • JMP_software: Question from a #SAS user at the #JMP booth: can JMP map zip codes around a specific regional area? Yes. http://t.co/mrmhkTVi #sasgf12 (24 Apr)
  • ma_ko: ggbio: An R implementation for extending the Grammar of Graphics for Genomic Data http://t.co/pSgA0T7v (24 Apr)
  • pchalasani: Kernel Functions for Machine Learning Applications http://t.co/HxeZ8JHC via @zite (23 Apr)
  • Biff_Bruise: RT @joceder Medical Outcomes Study: Measures of Quality of Life Core Survey from RAND Health | RAND http://t.co/bRLYjcxU (23 Apr)
  • freakonometrics: [free ebook] draft version of "An introduction to measure theory" by Terence Tao on his blog http://t.co/f4gNoDaC (from posts on his blog) (23 Apr)
  • recology_: @jebyrnes @DistribEcology perhaps could extend ggphylo (http://t.co/EyUA6ITM) to do SEM graphs? cc: @gjuggler (21 Apr)
  • DataJunkie: Excellent social resource for datasets: http://t.co/SktBDtdW (20 Apr)
  • therealprotonk: @onethingwell @JonMwords Here is a similar list, written as a bash script (so you could just run it in the terminal) https://t.co/CniFqMJu (19 Apr)
  • onethingwell: .osx - A treasure trove of OS X defaults write tweaks. http://t.co/4dcHoTFv (19 Apr)
  • FGRibreau: sigma.js - A lightweight JavaScript graph drawing library http://t.co/TxMpjChO (19 Apr)
  • Wiley_Stats: Read the Special Issue: Multiplicity Issues in Clinical Trials http://t.co/eZSDu4FH (19 Apr)
  • zoltanvarju: Word cloud alternatives http://t.co/f6QnLEzR #rstats (19 Apr)
  • ogrisel: Machine Learning with scikit-learn video tutorial by Jake VanderPlas at the #PyData Workshop in March: http://t.co/eViS1qrI #python (19 Apr)
  • noahWG: 1st large-scale, national clinical sequencing project searches for genes linked to mental disability: http://t.co/MjM7zdrB via @NatureNews (18 Apr)
  • freakonometrics: nice #rstats graphs, via http://t.co/82ojJBR3 http://t.co/4BlqC1lv (18 Apr)
  • ambrosebs: Some unit tests for Typed Clojure (subtyping, functions, parameterised types, expressions) https://t.co/kuHITHF0 (18 Apr)
  • gappy3000: Debugging code twice as hard as writing it. If you write code as smartly as you can, by definition you can't debug it. -B. Kernighan (17 Apr)
  • StatFact: The data may not contain the answer http://t.co/7L6kGLx0 (17 Apr)
  • zoltanvarju: Quil http://t.co/aHPXvITS (mix Processing Clojure) (14 Apr)
  • bigdata: FREE #ebook Mathematics for Computer Science: includes chapters on number & graph theory, asymptotics, combinatorics http://t.co/SJa8UEFf (14 Apr)
  • doryokujin: Visualization Techniques for Trees, Graphs, and Networks / “Chapter8_VisualizationTechniquesForTreesGraphsAndNetworks…” http://t.co/aVKrh9AK (14 Apr)
  • doryokujin: Designing Effective Visualizations / “Chapter12_DesigningEffectiveVisualization_355-377.pdf” http://t.co/9phUaYph (14 Apr)
  • patrickDurusau: Tutorial: Getting Started With Cassandra #topicmaps #nosql #Cassandra - http://t.co/vhB40SRg (13 Apr)
  • MonkScott: Online book: Learning Deep Architectures for AI http://t.co/vYdBzGnD #machinelearning (12 Apr)
  • zentree: "R, Julia and the shiny new thing" #rstats http://t.co/vGM6I2DX (12 Apr)
  • driven_by_data: How to use Twitter efficiently as social bookmarking service (including local full-text search) http://t.co/4QrSha8Z (10 Apr)
  • emacs_knight: How to learn Emacs - an online guide for beginners http://t.co/YQ4j9Yil (10 Apr)
  • agramfort: Biomedical Image Analysis Summer School, Paris, July 9-13, 2012, http://t.co/LduaY2lK (9 Apr)
  • yantonov: Lisp is so powerful that problems which are technical issues in other programming languages are social issues in Lisp. http://t.co/vu5kEFC4 (9 Apr)
  • RickWicklin: Whether you use #SAS, #RStats, or #MATLAB, vectorize your computations: The birthday matching problem (vectorized) http://t.co/Wt0nEAkZ (9 Apr)
  • cemerick: Making working with URLs in Clojure a little more pleasant: https://t.co/prm3YftM (9 Apr)
  • siah: The Lisp Curse http://t.co/tkCEQOr3 (9 Apr)
  • vsbuffalo: This is worrying. "at some point OS X will only run App Store approved software." MT @elehack: Apple vs. LaTeX. http://t.co/gpeaA9gU (9 Apr)
  • moorejh: I like Khoury's cautious optimism on the value of genetic testing for pop health. Right on target. http://t.co/estle2zk #genetics #genomics (8 Apr)
  • driven_by_data: .@JanWillemTulp Highly recommended: John P. Snyder – Map projections: A working manual http://t.co/CkCObn7y #free #ebook #cartography (8 Apr)
  • lordhaig: Sample size calculator http://t.co/P9IIOcn1 (7 Apr)
  • kshameer: Genetic mapping of complex traits: promises, problems, and prospects. http://t.co/fOyQHWqz (7 Apr)
  • JanWillemTulp: inspired by @driven_by_data's work on @kartographjs I'm learning more about map projections, for instance here: http://t.co/9fBHfcEr #gis (7 Apr)
  • psychepi: such a good paper! as tweeted in detail by @medskep MT @murzee @eqpaho Epidemiology, epigenetics & the Gloomy Prospect http://t.co/HAlk1QAO (7 Apr)
  • rOpenSci: Lots of updates to a long list of #rstats packages for #data and #sciencelit at GitHub http://t.co/fQ7h7Zns (7 Apr)
  • kshameer: Discovery and Preclinical Validation of Drug Indications Using Compendia of Public Gene Expression Data http://t.co/QiWVdrgq (7 Apr)
  • kshameer: Opportunities and challenges for the integration of massively parallel genomic sequencing into clinical practice:... http://t.co/WCLaa8cg (7 Apr)
  • kinggary: YourCast: Time Series Cross-Sectional Forecasting with Your Assumptions - version 1.5-1 http://t.co/wuZ8xfUj #rstats (6 Apr)
  • druvus: What everyone should know about genome scans http://t.co/jI9TCYGT #genomics (6 Apr)
  • jedisct1: Brute-forcing can be fast nowadays: http://t.co/Cx4ubejT (6 Apr)
  • emacs_knight: Try out C-x C-j (dired-jump) http://t.co/SrO30DCV #Emacs has no limits :-) (6 Apr)
  • siah: "An Introduction to Causal Inference" by Judea Pearl himself :) http://t.co/aOUi8jW2 (5 Apr)
  • geospacedman: @revodavid Three screenfuls, no diagrams, 9 lines of example code: http://t.co/J25prSbw (5 Apr)
  • johnmyleswhite: Moved optimization code for #julialang to http://t.co/WHAk1ebU Added gradient descent with back-tracking line search and constant step size. (5 Apr)
  • RickWicklin: Often a simple graph is more useful than a fancy one: Polar vs rectangular scatter plots http://t.co/IOTDlUeH #statistics (5 Apr)
  • Wiley_Stats: Using R and WinBUGS to fit a generalized partial credit model for developing and evaluating patient-reported outcomes http://t.co/sJe3YraR (5 Apr)
  • gappy3000: Berkeley Course of Alex Smola on scalable Machine Learning is on, with slides and videos http://t.co/tb6uUDSk (5 Apr)
  • neilfws: Penalized Logistic Regression for High-dimensional DNA Methylation Data with Case-Control Studies http://t.co/vcx6tYSH #citeulike (5 Apr)
  • walkingrandomly: OpenCL optimisation case study - fast Fourier transforms http://t.co/nWguCUob (5 Apr)
  • GaelVaroquaux: RT: @mpoullet The Sandbox : Banning LaTeX from the Mac App Store http://t.co/oUy1TzkJ = war on general purpose computing (5 Apr)
  • GreatestQuotes: "A man's errors are his portals of discovery." - James Joyce (5 Apr)
  • revodavid: Response to the great article by @surajgupta on the inner workings of R namespaces and environments: http://t.co/mEpg7FqB (5 Apr)
  • jameskeirstead: Pushed new commit on #rstats slopegraph to work with new #ggplot2 version https://t.co/AIGRjbbJ (4 Apr)
  • Stiivi: Brewery 0.8 Released - I’m glad to announce new release of Brewery – stream based data auditing and analysis... http://t.co/opOzCySx (4 Apr)
  • statsepi: My slowly growing list of free/open on-line resources for training in statistics. http://t.co/W0XXj1Zj #openaccess #openscience (4 Apr)
  • jedisct1: RT @nathanmarz: Research paper on using Storm, Hadoop, and HBase for social network analysis http://t.co/ZozfBDZv (3 Apr)
  • agramfort: Really nice intro slides to NiPype http://t.co/aDIJKVqC by Satra Ghosh (3 Apr)
  • tdhopper: 2 hour lecture on Optimization Algorithms in Machine Learning http://t.co/gxQSQy5B via @JeffLinderoth (3 Apr)
  • Stata: Stata Blog: The Penultimate Guide to Precision http://t.co/dTSvPPTj (3 Apr)
  • JanWillemTulp: this 3 hour introduction workshop of #pandas by @wesmckinn is fantastic! http://t.co/MXjyAIfi great to learn about data analysis in #python (3 Apr)
  • StatFact: RT @tdhopper: "…Models built with large amounts of data are often needlessly complex…" http://t.co/Yb5bsCy5 (3 Apr)
  • albertocairo: Article of the day: What @nytgraphics can teach you about visualization and graphics http://t.co/D9WrZwDz by @visualisingdata for @visually (3 Apr)
  • johnmyleswhite: I rewrote the ML4H Metropolis sampler example in #julialang. For speed, it blows the #rstats version out of the water: http://t.co/HsRwtThh (1 Apr)

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