This post is a lecture for IS624 Predictive Analytics, which is part of the CUNY Master’s program in Data Analytics. …Continue reading →

The anomalous package provides some tools to detect unusual time series in a large collection of time series. This is joint work with Earo Wang (an honours student at Monash) and Nikolay Laptev (from Yahoo Labs). Yahoo is interested in detecting unusual patterns in server metrics. The basic idea is to measure a range of

I was recently asked to write a survey on copulas for financial time series. The paper is, so far, unfortunately, in French, and is available on https://hal.archives-ouvertes.fr/. There is a description of various models, including some graphs and statistical outputs, obtained from read data. To illustrate, I’ve been using weekly log-returns of (crude) oil prices, Brent, Dubaï and Maya....

The dygraphs package is an R interface to the dygraphs JavaScript charting library. It provides rich facilities for charting time-series data in R, including: Automatically plots xts time-series objects (or objects convertible to xts). Rich interactive features including zoom/pan and series/point highlighting. Highly configurable axis and series display (including optional 2nd Y-axis). Display upper/lower bars (e.g. prediction

One of the things I’ve been trying to explore with my #f1datajunkie projects are ways of representing information that work both in a glanceable way as well as repaying deeper reading. I’ve also been looking at various ways of using text labels rather than markers to provide additional information around particular data points. For example,

The example below shows how to estimate a simple univariate Poisson time series model with the tscount package. While the model estimation is straightforward and yeilds very similar parameter estimates to the ones generated with the acp package (https://statcompute.wordpress.com/2015/03/29/autoregressive-conditional-poisson-model-i), the prediction mechanism is a bit tricky. 1) For the in-sample and the 1-step-ahead predictions: yhat_

A kind reader directed me in a comment on Experiments in Time Series Clustering to this paper. Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research Eamonn Keogh and Jessica Lin Computer Science & Engineering Department University of California – Riverside http://www.cs.ucr.edu/~eamonn/meaningless.pdf As I said in my last post, I don’t know...

Last night I spotted this tweet about the R package TSclust. Thank you Pablo and Jose for #TSclust - time series clustering package in #rstats ! http://t.co/GBQtQnQ8Lr— Pasha Roberts (@pasharoberts) March 2, 2015 I should start by saying that I really don’t know what I’m doing, so be warned. I thought it would interesting to apply TSclust to...

World wide quantitative easing does not seem to end. I live and work in Japan which has the lowest interest rate.Thanks to Quandl and RStudio, I can easily get the data of the interest rate and visualize it with R and dygraphs ...