Category Archives: regression

Phase Plane plots of COVID-19 deaths with uncertainties

Posted on 30 October 2020 by ecoquant

I. Introduction. It’s time to fulfill the promise made in “Phase plane plots of COVID-19 deaths“, a blog post from 2nd May 2020, and produce the same with uncertainty clouds about the functional trajectories(*). To begin, here are some assumptions … Continue reading →

Posted in American Statistical Association, Andrew Harvey, anomaly detection, count data regression, COVID-19, dependent data, dlm package, Durbin and Koopman, dynamic linear models, epidemiology, filtering, forecasting, Kalman filter, LaTeX, model-free forecasting, Monte Carlo Statistical Methods, numerical algorithms, numerical linear algebra, population biology, population dynamics, prediction, R, R statistical programming language, regression, statistical learning, stochastic algorithms | Tagged | Leave a comment

Calculating Derivatives from Random Forests

Posted on 27 June 2020 by ecoquant

(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 →

Posted in bridge to somewhere, Calculus, dependent data, dynamic generalized linear models, dynamical systems, ensemble methods, ensemble models, filtering, forecasting, hierarchical clustering, linear regression, model-free forecasting, Monte Carlo Statistical Methods, non-mechanistic modeling, non-parametric model, non-parametric statistics, numerical algorithms, prediction, R statistical programming language, random forests, regression, sampling, splines, statistical learning, statistical series, statistics, time derivatives, time series | Leave a comment

New COVID-19 incidence in the United States as AR(1) processes

Posted on 28 March 2020 by ecoquant

There are several sources of information regarding Covid-19 incidence now available. This post uses data from a single source: the COVID Tracking Project. In particular I restrict attention to cumulative daily case counts for the United States, the UK, and … Continue reading →

Posted in coronavirus, COVID-19, epidemiology, pandemic, regression, SARS-CoV-2 | Leave a comment