Time series

Descriptive statistics of some Agile feature characteristics

September 2, 2012 | Derek-Jones

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 ... [Read more...]

Visualizing Euro 2012: First Group Games

June 12, 2012 | diffuseprior

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, ... [Read more...]

Time-Series Policy Evaluation in R

May 21, 2012 | diffuseprior

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 ... [Read more...]

Temperature Change in Ireland

April 7, 2012 | diffuseprior

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 ... [Read more...]

non-stationary AR(10)

January 18, 2012 | xi'an

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 ... [Read more...]

Example 9.11: Employment plot

October 25, 2011 | Ken Kleinman

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...
[Read more...]

Generating restricted permutations with permute

October 18, 2011 | ucfagls

In a previous post I introduced the permute package and the function shuffle(). In that post I got as far as replicating R’s base function sample(). Here I’ll briefly outline how shuffle() can be used to generate restricted permutations. shuffle() … Continue reading → [Read more...]

Simple plot using R

September 21, 2011 | "We think therefore we R"

As a task for my Financial eco assignment I had to plot a simple time series of the overnight MIBOR(Mumbai interbank offer rates) for the past one year . The job could very well have been done easily in MS-Excel but I choose to plot it in R instea...
[Read more...]

Smoothing temporally correlated data

July 21, 2011 | ucfagls

Something I have been doing a lot of work with recently are time series data, to which I have been fitting additive models to describe trends and other features of the data. When modelling temporally dependent data, we often need … Continue reading → [Read more...]

Global warming since 1995 ‘now significant’

June 11, 2011 | ucfagls

Yesterday (June 11, 2011) the BBC reported on comments by Prof. Phil Jones, of the Climatic Research Unit (CRU), University of East Anglia (UEA), that the warming experienced by the planet since 1995 was statistically significant. That the trend in … Continue reading → [Read more...]

Time series

March 28, 2011 | xi'an

(This post got published on The Statistics Forum yesterday.) The short book review section of the International Statistical Review sent me Raquel Prado’s and Mike West’s book, Time Series (Modeling, Computation, and Inference) to review. The current post is not about this specific book, but rather on why ... [Read more...]

The housing bubble by city

March 17, 2011 | dan

The housing bubble by city. Miami sailed high and fell far. Detroit rose modestly and but dropped more than it went up. Dallas held steady. DC is enjoying a bit of renewed growth, but are in and New York yet to fall? [Read more...]


February 9, 2011 | Adam.Hyland

In time series work you often run into difficulties in modeling processes where the overall level of one variable (an input, for example) changes over time but the levels of another variable (an output) do not change. For instance if … Continue reading →
[Read more...]
1 2

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)