Posts Tagged ‘ books ’

what does more efficient Monte Carlo mean?

March 16, 2017
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what does more efficient Monte Carlo mean?

“I was just thinking that there might be a magic trick to simulate directly from this distribution without having to go for less efficient methods.” In a simple question on X validated a few days ago [about simulating from x²φ(x)] popped up the remark that the person asking the question wanted a direct simulation method […]

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Peter Lee (1940?-2017)

March 11, 2017
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Peter Lee (1940?-2017)

Just heard the sad news that Peter Lee, British Bayesian and author of Bayesian Statistics: An Introduction, has passed away yesterday night. While I did not know him, I remember meeting him at a few conferences in the UK and spending an hilarious evening at the pub. When the book came out, I thought it […]

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Peter Lee (1940?-2017)

March 11, 2017
By
Peter Lee (1940?-2017)

Just heard the sad news that Peter Lee, British Bayesian and author of Bayesian Statistics: An Introduction, has passed away yesterday night. While I did not know him, I remember meeting him at a few conferences in the UK and spending an hilarious evening at the pub. When the book came out, I thought it […]

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coauthorship and citation networks

February 20, 2017
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coauthorship and citation networks

As I discovered (!) the Annals of Applied Statistics in my mailbox just prior to taking the local train to Dauphine for the first time in 2017 (!), I started reading it on the way, but did not get any further than the first discussion paper by Pengsheng Ji and Jiashun Jin on coauthorship and […]

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coauthorship and citation networks

February 20, 2017
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coauthorship and citation networks

As I discovered (!) the Annals of Applied Statistics in my mailbox just prior to taking the local train to Dauphine for the first time in 2017 (!), I started reading it on the way, but did not get any further than the first discussion paper by Pengsheng Ji and Jiashun Jin on coauthorship and […]

Read more »

coauthorship and citation networks

February 20, 2017
By
coauthorship and citation networks

As I discovered (!) the Annals of Applied Statistics in my mailbox just prior to taking the local train to Dauphine for the first time in 2017 (!), I started reading it on the way, but did not get any further than the first discussion paper by Pengsheng Ji and Jiashun Jin on coauthorship and […]

Read more »

Reading Everything is Obvious by Duncan Watts

February 15, 2017
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Reading Everything is Obvious by Duncan Watts

In his book, Everything is Obvious (Once You Know the Answer): Why Common Sense Fails, Duncan Watts, a professor of sociology at Columbia, imparts urgent lessons that are as relevant to his students as to self-proclaimed data scientists. It takes only nominal effort to generate narrative structures that retrace the past, Watts contends, but developing lasting theory that produces valid predictions requires much more effort than common sense. Watts’s is…

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a knapsack riddle?

February 12, 2017
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a knapsack riddle?

The [then current now past] riddle of the week is a sort of multiarmed bandits optimisation. Of sorts. Or rather a generalised knapsack problem. The question is about optimising the allocation of 100 undistinguishable units to 10 distinct boxes against a similarly endowed adversary, when the loss function is and the distribution q of the […]

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an accurate variance approximation

February 6, 2017
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an accurate variance approximation

In answering a simple question on X validated about producing Monte Carlo estimates of the variance of estimators of exp(-θ) in a Poisson model, I wanted to illustrate the accuracy of these estimates against the theoretical values. While one case was easy, since the estimator was a Binomial B(n,exp(-θ)) variate [in yellow on the graph], […]

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a well-hidden E step

February 2, 2017
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a well-hidden E step

A recent question on X validated ended up being quite interesting! The model under consideration is made of parallel Markov chains on a finite state space, all with the same Markov transition matrix, M, which turns into a hidden Markov model when the only summary available is the number of chains in a given state […]

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