# Category Archives: time series

## “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

## “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,…

## 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

## 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

## Repeating Bullshit

Originally posted on Open Mind:
Question: How does a dumb claim go from just a dumb claim, to accepted canon by the climate change denialati? Answer: Repetition. Yes, keep repeating it. If it’s contradicted by evidence, ignore that or insult…

## 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

## Series, symmetrized Normalized Compressed Divergences and their logit transforms

(Major update on 11th January 2019. Minor update on 16th January 2019.) On comparing things The idea of a calculating a distance between series for various purposes has received scholarly attention for quite some time. The most common application is … Continue reading

## What are the odds of net zero?

What’s the Question? 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 … Continue reading

## `Letter to Lamar Smith’

On Ed Hawkins’ blog. The Committee on Science, Space & Technology of the US House of Representatives conducts regular evidence hearings on various science topics. On Wednesday 29th March, there is a hearing on “Climate science: assumptions, policy implications, and … Continue reading

## Energy Consumption with Air Source Heat Pumps and Water Heater

Once nice thing about having a net metered solar PV array is that, with a little diligence, you can figure out how much electricity your household is consuming each day, or at finer resolution if you like (*). Below is … Continue reading

## “All models are wrong. Some models are useful.” — George Box

(Image courtesy of the Damien Garcia.) As a statistician and quant, I’ve thought hard about that oft-cited Boxism. I’m not sure I agree. It’s not that there is such a thing as a perfect model, or correct model, whatever in … Continue reading

## “Predicting annual temperatures a year ahead” (Dr Gavin Schmidt at REALCLIMATE)

Dr Schmidt is essentially betting that the trend, seen as a random variable, will regress towards the smooth mean. I have a post at Nate Silver’s 538 site on how we can predict annual surface temperature anomalies based on El … Continue reading

## Bastardi’s Bust

Famous climate denialist Joe Bastari of WeatherBELL Analytics LLC, formerly of Accuweather.com made a prediction on Arctic ice recovery back in 2010 (when at AccuWeather), and observations have since made his “studies” laughable. I have heard his colleague, Joseph D’Aleo … Continue reading

## “Naïve empiricism and what theory suggests about errors in observed global warming”

A post from one of my favorite statistics-oriented bloggers, Variable Variability, dealing with a subject too casually passed over. See Naïve empiricism and what theory suggests about errors in observed global warming.

## Repaired R code for Markov spatial simulation of hurricane tracks from historical trajectories

(Slight update, 28th June 2020.) I’m currently studying random walk and diffusion processes and their connections with random fields. I’m interested in this because at the core of dynamic linear models, Kalman filters, and state-space methods there is a random … Continue reading

## A model of an electrical grid: A vision

Many people seem to view the electrical grid of the future being much like the present one. I think a lot about networks, because of my job. And I especially think a lot about network topologies, although primarily concerning the … Continue reading

## Bayesian blocks via PELT in R

Notice of Update I have made some changes to the Bayesian Blocks code linked from here, on 24th November 2021. Also I note the coming and going of a “BayesianBlocks” package on CRAN which contained an optinterval function also based upon … Continue reading

## “Full-depth Ocean Heat Content” reblog

This is a re-blog of an excellent post at And Then There’s Physics, titled Full-depth OHC or, expanded, “full-depth ocean heat content”. Since my holiday is now over, I thought I might briefly comment on a recent paper by Cheng … Continue reading

## “Stochastic Parameterization: Towards a new view of weather and climate models”

Judith Berner, Ulrich Achatz, Lauriane Batté, Lisa Bengtsson, Alvaro De La Cámara, Hannah M. Christensen, Matteo Colangeli, Danielle R. B. Coleman, Daan Crommelin, Stamen I. Dolaptchiev, Christian L.E. Franzke, Petra Friederichs, Peter Imkeller, Heikki Järvinen, Stephan Juricke, Vassili Kitsios, François … Continue reading

## On Smart Data

One of the things I find surprising, if not astonishing, is that in the rush to embrace Big Data, a lot of learning and statistical technique has been left apparently discarded along the way. I’m hardly the first to point … Continue reading

## “Catching long tail distribution” (Ted Dunning)

One of the best presentations on what can happen if someone takes a naive approach to network data. It also highlights what is, to my mind, the greatly underappreciated t-distribution, which is typically only used in connection with frequentist Student … Continue reading

## Six cases of models

The previous post included an attempt to explain land surface temperatures as estimated by the BEST project using a dynamic linear model including regressions on both quarterly CO2 concentrations and ocean heat content. The idea was to check the explanatory … Continue reading

## On Munshi mush

(Slightly updated on 2016-06-11.) Professor Emeritus Jamal Munshi of Sonoma State University has papers recently cited in science denier circles as evidence that the conventional associations between mean global surface temperature and cumulative carbon emissions are, well, bunk, due to … Continue reading