Hastie, Tibshirani and Friedman’s Elements of Statistical Learning first appeared in 2001 and is already a classic. It is my go-to book when I need a quick refresher on a machine learning algorithm. I like it because it is written using the language and perspective of statistics, and provides a ... [Read more...]

Who will win the SuperBowl this Sunday: Seattle or Denver? As pundits around the country weigh in with their predictions, you might want to check out the analysis from the New York Times' 4th Down Bot, which compares the coaches' calls on fourth down plays with what historical statistics and ... [Read more...]

Yesterday, we’ve seen how inference for time series was possible.  I started  with that one because it is actually the simple case. For instance, we can use ordinary least squares. There might be some possible bias (see e.g. White (1961)), but asymptotically, estimators are fine (consistent, with asymptotic normality). ... [Read more...]

James Taylor (@jamet123) is remarkable in capturing the nuances and mood of the data analytics and decision management industry and community. As a celebrated author and an avid writer, James has been writing more and more about the technologies that t... [Read more...]

Introduction It may be old news to some, but I just recently discovered that the automatic type inference system that R uses when parsing CSV files assumes that data sets will never contain 64-bit integer values. Specially, if an integer value read from a CSV file is too large to ... [Read more...]

Andrew and I have been discussing how we’re going to define functions in Stan for defining systems of differential equations; see our evolving ode design doc; comments welcome, of course. About Scope I mentioned to Andrew I would prefer pure lexical, static scoping, as found in languages like C++ ... [Read more...]

It’s been a while since a user of my plotting-functions asked whether it would be possible to compare multiple (generalized) linear models in one graph (see comment). While it is already possible to compare multiple models as table output, I now managed to build a function that plots several (... [Read more...]

In the course of this year, Dr. Luis Torgo will teach a Data Mining with R course together with the DIKW Academy in Nieuwegein, The Netherlands. Dr. Torgo is an Associate Professor at the department of Computer Science at the… See more › [Read more...]

Consider a (stationary) autoregressive process, say of order 2, for some white noise with variance . Here is a code to generate such a process, __ phi1=.25 __ phi2=.7 __ n=1000 __ set.seed(1) __ e=rnorm(n) __ Z=rep(0,n) __ for(t in 3:n) Z[t]=phi1*Z[t-1]+phi2*Z[t-2]+e[t] __ Z=Z[800:1000] __ ... [Read more...]

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At MCMSki IV, I attended (and chaired) a session where Martyn Plummer presented some developments on cut models. As I was not sure I had gotten the idea [although this happened to be one of those few sessions where [Read more...]

There is no shortage of time series data available on the web for use in student projects, or self-learning, or to test out new forecasting algorithms. It is now relatively easy to access these data sets directly in R. M Competition data The 1001 series from the M-competition and the 3003 series ... [Read more...]

Rasmus' post of last week on binomial testing made me think about p-values and testing again. In my head I was tossing coins, thinking about gender diversity and toast. The toast and tossing a buttered toast in particular was the most helpful thought experiment, as I didn't have a fixed ... [Read more...]

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Yesterday at the Davis R User’s Group1, Ryan Peek gave a talk about using the shiny package to create interactive web apps with R. Here are his slides. Ryan includes a bunch of links to examples and tutorials, as well as his own thermohydrographs app: Thanks to Revolution Analytics ... [Read more...]

Herbert Simon was succinct when he argued that judgment and choice "is shaped by a scissor whose two blades are the structure of the task environment and the computational capabilities of the actor" (Simon, 1990, p.7). As a marketing researcher, I take... [Read more...]

Few days ago I posted on doing a smart job on importing several data files alike from a directory. Today, I want to return to this topic, but stretching it a bit further by adding some complexity. I want to have a snapshot of the datasets even before starting work ... [Read more...]

In the MAT8595 course, we’ve seen yesterday Hill estimator of the tail index. To be more specific, we did see see that if , with , then Hill estimators for are given by for . Then we did say that satisfies some consistency in the sense that if , but not too fast, ... [Read more...]

by Daniel Hanson, QA Data Scientist, Revolution Analytics Introduction and Data Setup Last time, we included a couple of examples of plotting a single xts time series using the plot(.) function (ie, said function included in the xts package). Today, we’ll look at some quick and easy methods for ... [Read more...]

I've (passively) been keeping meticulous records of almost every song I've listened to since January of 2008. Since I opened my last.fm account 6 years ago, they've accumulated a massive detailed dataset of the 107,222 songs I've listened to since then. The best thing is that they're willing to share this data ... [Read more...]