(last updated 20th February 2020)

Reanalysis of business visits from deployments of a mobile phone app
This blog post regarding a reanalysis of a mobile phone app deployment and its related paper, “Multi-list Mark-Recapture methods: A semi-mathematical tutorial with illustrations”, is now available.

Causal inference for prediction of streamflows and other phenomena (tenative title, in progress)
This short-term project and activity has been started.

Cumulants and the Cornish-Fisher Expansion
This reports an investigation of moments of weighted Bernoulli variables, something which came up in online business decision-making.

On bag bans and sampling plans
A committee of the Town of Westwood, its Environmental Action Committee, sought to baseline shopping bag use prior to launching a campaign to promote bringing own bags to stores. They asked me to design a sampling plan which used the modest volunteer resources of the Committee to ascertain bag use rates by type. A follow-on study is begin planned to judge campaign effectiveness.

Stream flow and P-splines: Using built-in estimates for smoothing
An illustration of the use of penalized B-splines to produce best smooths for stream flows of Mother Brook in Dedham. The best smooths are picked using generalized cross-validation.

Series, symmetrized Normalized Compressed Divergences and their logit transforms

Procrustes tangent distance is better than SNCD

When linear systems can’t be solved by linear means

What are the odds of net zero?
A question was posed by a colleague a couple of months ago: What are the odds of a stock closing at the same price it opened? I found the question interesting, because, at first, it appeared to be a one-dimensional version of
another problem I looked at, which was in two dimensions. Well, I have produced an estimate, and am reporting results here. My first impressions of the problem were wrong. It actually is a two dimensional problem, not a one dimensional one. And it is not the same as the earlier problem, because although one of its dimensions is discrete, the other, time, is (essentially) continuous. I explain at the post.

Repaired R code for Markov spatial simulation of hurricane tracks from historical trajectories
How well can simply data sets of where hurricanes have been predict where they might go?

Why smooth?
Uniform sampling of a disk, and implications for sampling the Internet

A look at an electricity consumption series using SNCDs for clustering

HadCRUT4 and GISTEMP series filtered and estimated with simple RTS model
The HADCRUT4 and GISTEMP series are two prominent time series for global temperature. This study examines use of dynamic linear models for smoothing these series, estimating their uncertainties in the smooth, and then calculating a Bayesian combined smooth using both series together.

Illustrating particle filters and Bayesian fusion using successive location estimates on the unit circle

Blind Bayesian recovery of components of residential solid waste tonnage from totals data

JAGS for finding Highs and Lows in a week of Wikipedia accesses

Bayesian Bootstrap

On Dangers of Indiscriminate Clustering

On differential localization of tumors using relative concentrations of ctDNA. Part 1.

On differential localization of tumors using relative concentrations of ctDNA. Part 2.

dynamic linear model applied to sea-level-rise anomalies

On Munshi mush

Six cases of models

Bayesian blocks via PELT in R

climate internal variability is just residual variance from modeling with a smooth curve?

Sea Level Rise, after Church and White (2006)

Dynamic Linear Models package, dlmodeler

Comprehensive and compact tutorial on Petris’ DLM package in R; with an update about Helske’s KFAS
This is easily my most popular blog post, along with Dynamic Linear Models package, dlmodeler, in the United States and internationally.

A trivariate, coupled dynamical system, and hints for using the carbon cycle to explain glacial-interglacial periods

Less evidence for a global warming hiatus, and urging more use of Bayesian model averaging in climate science

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