Posts Tagged ‘ Time series ’

Inference and autoregressive processes

September 6, 2012
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Inference and autoregressive processes

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=.5 > phi2=-.4 > sigma=1.5 > set.seed(1) > n=240 > WN=rnorm(n,sd=sigma) > ...

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Descriptive statistics of some Agile feature characteristics

September 2, 2012
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Descriptive statistics of some Agile feature characteristics

The purpose of software engineering research is to figure out how software development works so that the software industry can improve its quality/timeliness (i.e., lower costs and improved customer satisfaction). Research is hampered by the fact that companies are not usually willing to make public good quality data about the details of their software development

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Visualizing Euro 2012: First Group Games

June 12, 2012
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Visualizing Euro 2012: First Group Games

Now that every team has played a match it will be interesting to see how this has affected the (inverse) odds of victory. Since the plot in my last post was a bit ‘busy’, I have decided to use the facet_wrap function in gglplot2 to stratify by group. Also, re-producing the ‘busy’ plot from the

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Time series cross-validation 4: forecasting the S&P 500

June 11, 2012
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Time series cross-validation 4: forecasting the S&P 500

I finally got around to publishing my time series cross-validation package to github, and I plan to push it out to CRAN  shortly. You can clone the repo using github for mac, for windows, or linux, and then run the following script to...

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Time-Series Policy Evaluation in R

May 21, 2012
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Time-Series Policy Evaluation in R

Quantifying the success of government policies is clearly important. Randomized control trials, like those conducted by drug companies, are often described as the ‘gold-standard’ for policy evaluation. Under these, a policy is implemented in/to one area/group (treatment), but not in/to another (control). The difference in outcomes between the two areas or groups represents the effectiveness

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Temperature Change in Ireland

April 7, 2012
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Temperature Change in Ireland

Has Ireland gotten any warmer? Ask any punter on the street and they will happily inform you of wild swings, trends and dips. “Back when I was a child”, “when I was younger”, or “years ago” are the usual refrains. What’s the evidence? To answer this, I will use the temperature data from my previous

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Time Series Intervention Analysis wih R and SAS

January 21, 2012
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Time Series Intervention Analysis wih R and SAS

In a previous post, I worked through the theory behind intervention analysis. In his time series course, University of Georgia political science professor Jamie Monogan demonstrates how to implement intervention analysis in R.  The following examp...

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non-stationary AR(10)

January 18, 2012
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non-stationary AR(10)

In the revision of Bayesian Core on which Jean-Michel Marin and I worked together most of last week, having missed our CIRM break last summer (!), we have now included an illustration of what happens to an AR(p) time series when the customary stationarity+causality condition on the roots of the associated polynomial is not satisfied. 

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Functional and Parallel time series cross-validation

November 21, 2011
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Functional and Parallel time series cross-validation

Rob Hyndman has a great post on his blog with example on how to cross-validate a time series model.  The basic concept is simple:  You start with a minimum number of observations (k), and fit a model (e.g. an arima model) to those observation...

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Example 9.11: Employment plot

October 25, 2011
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Example 9.11: Employment plot

A facebook friend posted the picture reproduced above-- it makes the case that President Obama has been a successful creator of jobs, and also paints GW Bush as a president who lost jobs. Another friend pointed out that to be fair, all of Bush's presi...

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