Category Archives: statistical models

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

Posted in alternatives to the Green New Deal, American Association for the Advancement of Science, climate change, climate denial, climate education, climate policy, climate science, David Spiegelhalter, dynamical systems, fluid dynamics, games of chance, global warming, global weirding, IPCC, model comparison, risk, Risky Talk, statistical models, statistical series | Leave a comment

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

Posted in American Association for the Advancement of Science, American Statistical Association, anti-intellectualism, anti-science, climate denial, corruption, data science, data visualization, Donald Trump, dump Trump, epidemiology, experimental science, exponential growth, forecasting, Kalman filter, model-free forecasting, nonlinear systems, open data, penalized spline regression, population dynamics, sampling algorithms, statistical ecology, statistical models, statistical regression, statistical series, statistics, sustainability, the right to know, the stack of lies | 1 Comment

“Code for causal inference: Interested in astronomical applications”

via Code for causal inference: Interested in astronomical applications From Professor Ewan Cameron at his Another Astrostatistics Blog.

Posted in American Association for the Advancement of Science, American Statistical Association, astronomy, astrostatistics, causal inference, causation, counterfactuals, epidemiology, experimental design, experimental science, multivariate statistics, prediction, propensity scoring, quantitative biology, quantitative ecology, reproducible research, rhetorical mathematics, rhetorical science, rhetorical statistics, science, statistical ecology, statistical models, statistical regression, statistics | Leave a comment

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

Posted in Bayesian computational methods, biology, capture-mark-recapture, capture-recapture, Christian Robert, count data regression, cumulants, diffusion, diffusion processes, Ecological Society of America, ecology, epidemiology, experimental science, field research, Gibbs Sampling, Internet measurement, Jean-Michel Marin, linear regression, mark-recapture, mathematics, maximum likelihood, Monte Carlo Statistical Methods, multilist methods, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerics, open source scientific software, Pierre-Simon Laplace, population biology, population dynamics, quantitative biology, quantitative ecology, R, R statistical programming language, sampling, sampling algorithms, segmented package in R, statistical ecology, statistical models, statistical regression, statistical series, statistics, stepwise approximation, stochastic algorithms, surveys, V. M. R. Muggeo | 1 Comment

“Bayesian replication analysis” (by John Kruschke)

“… the ability to express [hypotheses] as distributions over parameters …” Bayesian estimation supersedes the t-test: (Also by Professor Kruschke.)

Posted in American Statistical Association, Bayesian, John Kruschke, model comparison, rationality, rhetorical statistics, statistical models, statistics, Student t distribution | Leave a comment

Cumulants and the Cornish-Fisher Expansion

“Consider the following.” (Bill Nye the Science Guy) There are random variables drawn from the same kind of probability distribution, but with different parameters for each. In this example, I’ll consider random variables , that is, each drawn from a … Continue reading

Posted in Calculus, closed-form expressions, Cornish-Fisher expansion, cumulants, descriptive statistics, mathematics, maths, multivariate statistics, statistical models, statistics, theoretical statistics | Leave a comment