Peter's stats stuff

Applying statistics and data science 'in the wild'

I write about applications of data and analytical techniques like statistical modelling and simulation to real-world situations. I show how to access and use data, and provide examples of analytical products and the code that produced them.

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Recent posts

Moving largish data from R to H2O - spam detection with Enron emails

18 February 2017

I finally solve my problem of writing large sparse matrices from R into SVMLight format for importing to H2O; and demonstrate application with spam detection trained on the Enron email data comparing a generalized linear model, random forest, gradient boosting machine, and deep neural network.

US Presidential inauguration speeches

23 January 2017

I do some basic textual analysis and visualization with US Presidential inauguration speeches.

Does seasonally adjusting first help forecasting?

22 January 2017

I test some forecasting models on nearly 3,000 seasonal timeseries to see if it's better to seasonally adjust first or to incorporate the seasonality into the model used for forecasting. Turns out it is marginally better to seasonally adjust beforehand when using an ARIMA model and it doesn't matter with exponential smoothing state space models. Automated use of Box-Cox transformations also makes forecasts with these test series slightly worse. The average effects were very small, and dwarfed by different performance on different domains and frequency of data.

Books I like

14 January 2017

My ten recommended books for applied statistics and data science. Then 13 more!

Cross-validation of topic modelling

05 January 2017

Cross-validation of the "perplexity" from a topic model, to help determine a good number of topics.

Sparse matrices, k-means clustering, topic modelling with posts on the 2004 US Presidential election

31 December 2016

I explore different sparse matrix formats in R and moving data from R to H2O. Along the way I use k-means clustering and topic modelling to explore textual data from the Daily Kos blog on the 2004 US Presidential election.

Extracting data on shadow economy from PDF tables

26 December 2016

The shadow economy as a percentage of GDP in wealthier countries is in decline; and had a spike in 2009 with the economic crisis. More research is needed to adequately understand it. Along the way I experiment with extracting data frames from PDF tables; and show it's always worthwhile looking at the same data in different ways, which can be as simple as freeing up the vertical axes of graphics.

forecastHybrid 0.3.0 on CRAN

24 December 2016

forecastHybrid 0.3.0 for ensemble time series forecasting is now on CRAN. Two new features are prediction intervals for the nnetar (neural network) component of the combination; and theta method models.

Air quality in Indian cities

18 December 2016

Air pollution in Indian cities is unambiguously seasonal, and also might have a Diwali impact.

Extrapolation is tough for trees!

10 December 2016

Tree-based predictive analytics methods like random forests and extreme gradient boosting may perform poorly with data that is out of the range of the original training data.