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comments on Watson and Holmes

April 1, 2016

“The world is full of obvious things which nobody by any chance ever observes.” The Hound of the Baskervilles In connection with the incoming publication of James Watson’s and Chris Holmes’ Approximating models and robust decisions in Statistical Science, Judith Rousseau and I wrote a discussion on the paper that has been arXived yesterday. “Overall, […]

Holmes alone

November 29, 2020

From reading a rather positive review in The New York Times (if less in The Guardian, which states that it all rattles along amiably enough!), and my love of everything Holmes (if not as much as George Casella!), I watched Enola Holmes almost as soon as it came out on Netflix. While the film was […]

journal of the [second] plague year [con’d]

April 24, 2021

Read The Office of Gardens and Ponds (in French), by Didier Decoin [whom John l’Enfer I read more than forty years ago, with no lasting memories!], another random book found in the exchange section of our library!  While a pastiche of Japanese travel novels, the book is quite enjoyable and reminded me of our hike […]

a computational approach to statistical learning [book review]

April 15, 2020

This book was sent to me by CRC Press for review for CHANCE. I read it over a few mornings while [confined] at home and found it much more computational than statistical. In the sense that the authors go quite thoroughly into the construction of standard learning procedures, including home-made R codes that obviously help […]

Why should I be Bayesian when my model is wrong?

May 9, 2017

Guillaume Dehaene posted the above question on X validated last Friday. Here is an except from it: However, as everybody knows, assuming that my model is correct is fairly arrogant: why should Nature fall neatly inside the box of the models which I have considered? It is much more realistic to assume that the real […]