1674 search results for "Time Series"

CausalImpact: A new open-source package for estimating causal effects in time series

September 10, 2014
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CausalImpact: A new open-source package for estimating causal effects in time series

How can we measure the number of additional clicks or sales that an AdWords campaign generated? How can we estimate the impact of a new feature on app downloads? How do we compare the effectiveness of publicity across countries?In principle, all of these questions can be answered through causal inference.In practice, estimating a causal effect...

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Specifying complicated groups of time series in hts

June 14, 2014
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With the latest version of the hts package for R, it is now possible to specify rather complicated grouping structures relatively easily. All aggregation structures can be represented as hierarchies or as cross-products of hierarchies. For example, a hierarchical time series may be based on geography: country, state, region, store. Often there is also a separate product hierarchy: product...

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Identifying periods of change in time series with GAMs

May 15, 2014
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Identifying periods of change in time series with GAMs

In previous posts (here and here) I looked at how generalized additive models (GAMs) can be used to model non-linear trends in time series data. In my previous post I extended the modelling approach to deal with seasonal data where we model both the within year (seasonal) and between year (trend) variation with separate smooth functions....

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Seasonal, or periodic, time series

March 20, 2014
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Seasonal, or periodic, time series

Monday, in our MAT8181 class, we’ve discussed seasonal unit roots from a practical perspective (the theory will be briefly mentioned in a few weeks, once we’ve seen multivariate models). Consider some time series , for instance traffic on French roads, > autoroute=read.table( + "http://freakonometrics.blog.free.fr/public/data/autoroute.csv", + header=TRUE,sep=";") > X=autoroute$a100 > T=1:length(X) > plot(T,X,type="l",xlim=c(0,120)) > reg=lm(X~T) > abline(reg,col="red") As discussed in a...

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Displaying time series, spatial, and space-time data with R is available for pre-order

Displaying time series, spatial, and space-time data with R is available for pre-order

Two years ago, motivated by a proposal from John Kimmel, Executive Editor at Chapman & Hall/CRC Press, I started working …Sigue leyendo →

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Fitting models to short time series

March 3, 2014
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Fitting models to short time series

Following my post on fitting models to long time series, I thought I’d tackle the opposite problem, which is more common in business environments. I often get asked how few data points can be used to fit a time series model. As with almost all sample size questions, there is no easy answer. It depends on the number of model parameters...

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More time series data online

February 27, 2014
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Earlier this week I had coffee with Ben Fulcher who told me about his online collection comprising about 30,000 time series, mostly medical series such as ECG measurements, meteorological series, birdsong, etc. There are some finance series, but not ma...

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Nonlinear Time Series just appeared

February 25, 2014
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Nonlinear Time Series just appeared

My friends Randal Douc and Éric Moulines just published this new time series book with David Stoffer. (David also wrote Time Series Analysis and its Applications with Robert Shumway a year ago.) The books reflects well on the research of Randal and Éric over the past decade, namely convergence results on Markov chains for validating

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demodulating time series

February 17, 2014
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demodulating time series

This posting shows how one might perform demodulation in R. It is assumed that readers are generally familiar tith the procedure. First, create some fake data, a carrier signal with period 10, modulated over a long timescale, and with phase drifting linearly over time. 1 2 3 4 5 6 7 8 9 10 period <- 10 fc <- 1/period fs <- 1 n...

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Automatic time series forecasting in Granada

January 30, 2014
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In two weeks I am presenting a workshop at the University of Granada (Spain) on Automatic Time Series Forecasting. Unlike most of my talks, this is not intended to be primarily about my own research. Rather it is to provide a state-of-the-art overview of the topic (at a level suitable for Masters students in Computer Science). I thought I’d provide...

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