Posts Tagged ‘ Poisson distribution ’

fine-sliced Poisson [a.k.a. sashimi]

March 19, 2014
By
fine-sliced Poisson [a.k.a. sashimi]

As my student Kévin Guimard had not mailed me his own Poisson slice sampler of a Poisson distribution, I could not tell why the code was not working! My earlier post prompted him to do so and a somewhat optimised version is given below: As you can easily check by running the code, it does […]

Read more »

sliced Poisson

March 17, 2014
By
sliced Poisson

One of my students complained that his slice sampler of a Poisson distribution was not working when following the instructions in Monte Carlo Statistical Methods (Exercise 8.5). This puzzled me during my early morning run and I checked on my way back, even before attacking the fresh baguette I had brought from the bakery… The […]

Read more »

Modelling Olympic Medal Wins

February 10, 2014
By
Modelling Olympic Medal Wins

With the Sochi Winter Olympics now well underway, I was reminded of the empirical literature that has attempted to model the number of medals that different countries win.Back in 2006, one of our students, Glen Roberts, wrote an excellent paper, titled...

Read more »

Checking the Goodness of Fit of the Poisson Distribution in R for Alpha Decay by Americium-241

Checking the Goodness of Fit of the Poisson Distribution in R for Alpha Decay by Americium-241

Introduction Today, I will discuss the alpha decay of americium-241 and use R to model the number of emissions from a real data set with the Poisson distribution.  I was especially intrigued in learning about the use of Am-241 in smoke detectors, and I will elaborate on this clever application.  I will then use the Pearson chi-squared […]

Read more »

optimising accept-reject

November 20, 2012
By
optimising accept-reject

I spotted on R-bloggers a post discussing optimising the efficiency of programming accept-reject algorithms. While it is about SAS programming, and apparently supported by the SAS company, there are two interesting features with this discussion. The first one is about avoiding the dreaded loop in accept-reject algorithms. For instance, taking the case of the truncated-at-one [...]

Read more »


Subscribe

Email:

  Subscribe