# Category Archives: statistical series

## “Trump supporters go to Washington”

People don’t only have to worry about a government tracking them by their smartphones. In this case, the social effects of this capability were beneficial, because “some very bad dudes” were able to be found and identified. But most people … Continue reading

## “Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions”

J. Dehning et al., Science 369, eabb9789 (2020). DOI: 10.1126/science.abb9789 Source code and data. Note: This is not a classical approach to assessing strength of interventions using either counterfactuals or other kinds of causal inference. Accordingly, the argument for the … Continue reading

## Calculating Derivatives from Random Forests

(Comment on prediction intervals for random forests, and links to a paper.) (Edits to repair smudges, 2020-06-28, about 0945 EDT. Closing comment, 2020-06-30, 1450 EDT.) There are lots of ways of learning about mathematical constructs, even about actual machines. One … Continue reading

## Great podcast: “Confronting uncertainty with Tamsin Edwards”

Dr Tamsin Edwards visits Professor David Spiegelhalter on his “Risky Talk” podcast. Dr Edwards is a climate scientist with the title Senior Lecturer in Physical Geography at Kings College, London. There’s much good talk about climate and its associated uncertainties, … Continue reading

## COVID-19 statistics, a caveat : Sources of data matter

There are a number of sources of COVID-19-related demographics, cases, deaths, numbers testing positive, numbers recovered, and numbers testing negative available. Many of these are not consistent with one another. One could hope at least rates would be consistent, but … Continue reading

## “Lockdown WORKS”

Originally posted on Open Mind:
Over 2400 Americans died yesterday from Coronavirus. Here are the new deaths per day (“daily mortality”) in the USA since March 10, 2020 (note: this is an exponential plot) As bad as that news is,…

## What happens when time sampling density of a series matches its growth

This is the newly updated map of COVID-19 cases in the United States, updated, presumably, because of the new emphasis upon testing: How do we know this is the recent of recent testing? Look at the map of active cases: … Continue reading

## Reanalysis of business visits from deployments of a mobile phone app

Updated, 20th October 2020 This reports a reanalysis of data from the deployment of a mobile phone app, as reported in: M. Yauck, L.-P. Rivest, G. Rothman, “Capture-recapture methods for data on the activation of applications on mobile phones“, Journal … Continue reading

## A response to a post on RealClimate

(Updated 2342 EDT, 28 June 2019.) This is a response to a post on RealClimate which primarily concerned economist Ross McKitrick’s op-ed in the Financial Post condemning the geophysical community for disregarding Roger Pielke, Jr’s arguments. Pielke, in that link, … Continue reading

## California Marine Debris Prevention: Banning Plastic Bags is Not Enough

NOAA has a full page of videos on marine debris and how to prevent it. The state of California has a 2018 plan on preventing marine debris. Here are some highlights. There is a good deal more in the report, … Continue reading

## Procrustes tangent distance is better than SNCD

I’ve written two posts here on using a Symmetrized Normalized Compression Divergence or SNCD for comparing time series. One introduced the SNCD and described its relationship to compression distance, and the other applied the SNCD to clustering days at a … Continue reading

## Stream flow and P-splines: Using built-in estimates for smoothing

Mother Brook in Dedham Massachusetts was the first man-made canal in the United States. Dug in 1639, it connects the Charles River at Dedham, to the Neponset River in the Hyde Park section of Boston. It was originally an important … Continue reading

## A look at an electricity consumption series using SNCDs for clustering

(Slightly amended with code and data link, 12th January 2019.) Prediction of electrical load demand or, in other words, electrical energy consumption is important for the proper operation of electrical grids, at all scales. RTOs and ISOs forecast demand based … Continue reading