Revolution R: 100% R and More – slides and replay

August 26, 2011
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If you missed this week's webinar, the slides from my presentation Revolution R Enteprise: 100% R and More may be useful as an introduction to R and the additional capabilities of Revolution R Enterprise. The slides themselves and the replay video are also available for download from the link below. Revolution Analytics webinars: Revolution R Enterprise: 100% R and...

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9 more ways to bring data into R

August 26, 2011
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Here's a followup to yesterday's post on using the rdatamarket package to import data into R. Ajay Ohri at the DecisionStats blog offers nine additional methods for bringing data into R, from sources including InfoChimps, the Google Prediction API, the World Bank World Development Indicators, Bloomberg Market Data, and much more. See Ajay's post at the link below for...

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Because it’s Friday: Spurious correlation edition

August 26, 2011
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Because it’s Friday: Spurious correlation edition

If the Flight of the Concords taught me anything, it's that you can't trust Australians. This morning I was poking around the DataMarket site, when I noticed something suspicious about Australian sheep production: I decided to investigate further: ju...

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FishBASE from R

August 26, 2011
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FishBASE from R

In lab known for its quality data collection, high-speed video style, writing the weekly blog post can be a bit of a challenge for the local code monkey. That’s right, no videos today. But lucky for me, even this group … Continue reading →

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Fourier-Motzkin elimination with the editrules package

August 26, 2011
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Last week I talked about our editrules package at the useR!2011 conference. In the coming time I plan to write a short series of blogs about the functionality of editrules. Below I describe the eliminate and isFeasible functions. But first: … Continue reading →

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Fourier-Motzkin elimination with the editrules package

August 26, 2011
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Fourier-Motzkin elimination with the editrules package

Last week I talked about our editrules package at the useR!2011 conference. In the coming time I plan to write a short series of blogs about the functionality of editrules. Below I describe the eliminate and isFeasible functions. But first: a bit ...

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A first go at ‘manipulate’ in RStudio

August 26, 2011
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A first go at ‘manipulate’ in RStudio

Something I’m missing from R (especially coming from Mathematica) is the ability to quickly build interactive graphs, which I find very useful for getting a good intuition of the impact of parameters on a mathematical function. Richie Cotton’s post about … Continue reading →

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Quick labels within figures

August 26, 2011
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Quick labels within figures

One of the coolest R packages I heard about at the useR! Conference: Toby Dylan Hocking‘s directlabels package for putting labels directly next to the relevant curves or point clouds in a figure. I think I first learned about this idea from Andrew Gelman: that a separate legend requires a lot of back-and-forth glances, so

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Friday quote: what is the question to which this number is the answer?

August 26, 2011
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Friday quote: what is the question to which this number is the answer?

John Kay muses on interpreting statistical data: Always ask of such data “what is the question to which this number is the answer?”. “Earnings before interest, tax, depreciation and amortisation on a like-for-like basis before allowance for exceptional restructuring costs” is the answer to the question “what is the highest profit number we can present without attracting...

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Friday quote: what is the question to which this number is the answer?

August 26, 2011
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Friday quote: what is the question to which this number is the answer?

John Kay muses on interpreting statistical data: Always ask of such data “what is the question to which this number is the answer?”. “Earnings before interest, tax, depreciation and amortisation on a like-for-like basis before allowance for exceptional restructuring costs” is the answer to the question “what is the highest profit number we can present without attracting flat disbelief?”.

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Le Monde puzzle [#737]

August 26, 2011
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Le Monde puzzle [#737]

The puzzle in the weekend edition of Le Monde this week can be expressed as follows: Consider four integer sequences (xn), (yn), (zn), and (wn), such that and, if u=(xn,yn,zn,wn), for i=1,…,4, if ui is not the maximum of u and otherwise. Find the first return time n (if any) such that xn=0. Find the value

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Time series cross-validation: an R example

August 25, 2011
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Time series cross-validation: an R example

I was recently asked how to implement time series cross-validation in R. Time series people would normally call this “forecast evaluation with a rolling origin” or something similar, but it is the natural and obvious analogue to leave-one-out cross-validation for cross-sectional data, so I prefer to call it “time series cross-validation”. Here is some example

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Examples on Clustering with R

August 25, 2011
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Examples on Clustering with R

R code examples on various clustering techniques are available as “Clustering in R” in Chapter 4 of R & Bioconductor Manual by Thomas Girke, UC Riverside. It provides R examples on - Hierarchical Clustering, including tree cutting/coloring and heatmaps, - … Continue reading →

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Mode vs Mean in Tactical Allocation

August 25, 2011
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Mode vs Mean in Tactical Allocation

Let’s take Modest Modeest for Moving Average one step further and use it in a basic tactical allocation system using Vanguard funds.  THIS IS NOT INVESTMENT ADVICE AND VERY EASILY MIGHT CAUSE LARGE LOSSES.  VANGUARD FUNDS IMPOSE EARLY REDEM...

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Major changes to the forecast package

August 25, 2011
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Major changes to the forecast package

The forecast package for R has undergone a major upgrade, and I’ve given it version number 3 as a result. Some of these changes were suggestions from the forecasting workshop I ran in Switzerland a couple of months ago, and some have been on the drawing board for a long time. Here are the main

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String functions in R

August 25, 2011
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Here's a quick cheat-sheet on string manipulation functions in R, mostly cribbed from Quick-R's list of String Functions with a few additional links. substr(x, start=n1, stop=n2) grep(pattern,x, value=FALSE, ignore.case=FALSE, fixed=FALSE) gsub(pattern, replacement, x, ignore.case=FALSE, fixed=FALSE) gregexpr(pattern, text, ignore.case=FALSE, perl=FALSE, fixed=FALSE) strsplit(x, split) paste(..., sep="", collapse=NULL) sprintf(fmt, ...)

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How to access 100M time series in R in under 60 seconds

August 25, 2011
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How to access 100M time series in R in under 60 seconds

DataMarket, a portal that provides access to more than 14,000 data sets from various public and private sector organizations, has more than 100 million time series available for download and analysis. (Check out this presentation for more info about DataMarket.) And now with the new package rdatamarket, it's trivially easy to import those time series into R for charting,...

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Numerical analysis for statisticians

August 25, 2011
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Numerical analysis for statisticians

“In the end, it really is just a matter of choosing the relevant parts of mathematics and ignoring the rest. Of course, the hard part is deciding what is irrelevant.” Somehow, I had missed the first edition of this book and thus I started reading it this afternoon with a newcomer’s eyes (obviously, I will

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Benford’s law, or the First-digit law

August 25, 2011
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Benford’s law, or the First-digit law

Benford's law, also called the first-digit law, states that in lists of numbers from many (but not all) real-life sources of data, the leading digit is distributed in a specific, non-uniform way. According to this law, the first digit is 1 about 30% of the time, and larger digits occur as the leading digit with lower and lower frequency,...

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Forecasting in R: Modeling GDP and dealing with trend.

August 25, 2011
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Forecasting in R: Modeling GDP and dealing with trend.

Okay so we want to forecast GDP. How do we even begin such a burdensome ordeal?Well each time series has 4 components that we wish to deal with and those are seasonality, trend, cyclicality and error.  If we deal with seasonally adjusted data we d...

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Roger Herriot Award

August 25, 2011
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At the Joint Statistical Meetings (Aug 2011), accepting the Roger Herriot Award for Innovation in Federal Statistics, I tipped my hat to pen-source software and three mentors.  I use the software (R, OpenBUGS, and MediaWiki) every d...

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"My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]: —Data is the most…"

August 25, 2011
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"My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]: —Data is the most…"

“My interpretation of grammar : —Data is the most important thing, and the thing that you bring to the table. —Geometric objects … what you actually see on the plot: points, lines, polygons, etc. ...

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"My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]: —Data is the most…"

August 25, 2011
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"My interpretation of [Leland Wilkinson’s] grammar [of statistical graphics]:
—Data is the most…"

“My interpretation of grammar : —Data is the most important thing, and the thing that you bring to the table. —Geometric objects … what you actually see on the plot: points, lines, polygons, etc. ...

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Reproducible Econometric Research

August 25, 2011
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I doubt if anyone would deny the importance of being able to reproduce one's econometric results. More importantly, other researchers should be able to reproduce our results to verify (a) that we've done what we said we did; (b) to investigate the sensitivity of our results to the various choices we made (e.g., functional form of our model, choice...

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Comparison of ave, ddply and data.table

August 25, 2011
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Comparison of ave, ddply and data.table

A guest post by Paul Hiemstra. ———— Fortran and C programmers often say that interpreted languages like R are nice and all, but lack in terms of speed. How fast something works in R greatly depends on how it is implemented, i.e. which packages/functions does one use. A prime example, which shows up regularly on

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computational difficulties [with notations]

August 25, 2011
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computational difficulties [with notations]

Here is an email I received from Umberto: I have a doubt regarding the tempered transitions method you considered in your JASA article with Celeux and Hurn. On page 961 you detail the several steps for building a proposal for a given distribution by simulating through l tempered power densities. I am slightly confused regarding

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Things I learned at useR!2011

August 25, 2011
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Things I learned at useR!2011

The title says “things” but conferences are mainly about people. Some of it can be serendipitous.  For example, one day I sat next to Jonathan Rougier at lunch because I had a question for him about climate models.  When Jonathan left, I started a conversation with the person on my other side.  That was most … Continue reading...

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Forecasting time series using R

August 24, 2011
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I’ll be giving a talk on Forecasting time series using R for the Melbourne Users of R Network (MelbURN) on Thursday 27 October 2011 at 6pm. I will look at the various facilities for time series forecasting available in R, concentrating on the forecast package. This package implements several automatic methods for forecasting time series

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Modest Modeest for Moving Average

August 24, 2011
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Modest Modeest for Moving Average

I have no idea who originated the idea of using moving averages to determine entry and exit points in a trading system.  I do know that Mebane Faber (briefly discussed in Shorting Mebane Faber) has recently popularized the notion through his >7...

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