If you can write the likelihood function for your model, MHadaptive will take care of the rest (ie. all that MCMC business). I wrote this R package to simplify the estimation of posterior distributions of arbitrary models. Here’s how it works: 1) Define your model (ie the likelihood * prior). In this example, lets...
(Almost) every introductory course in probability introduces conditional probability using the famous Monte Hall problem. In a nutshell, the problem is one of deciding on a best strategy in a simple game. In the game, the contestant is asked to select one of three doors. Behind one of the doors is a great prize...
By following twitter’s #rstats hashtag (rss feed), I recently came across a very interesting R-related blog: datanalytics.com. The first post I read from it was about setting up an on-line reading group to go through the excellent “The Elements of … Continue reading →
I love board games. Over the holidays, I came across this interesting post over at Arthur Charpentier’s Freakonometrics blog about the classic game of snakes and ladders. The post is a nice little demonstration of how the game can be formulated completely as a Markov chain, and can be analysed simply using the mathematics...
Teacher: “How variable is your estimate of the mean?” Student: “Uhhh, it’s not. I took a sample and calculated the sample mean. I only have one number.” Teacher: “Yes, but what is the standard deviation of sample means?” Student: “What do you mean means, I only have the one friggin number.” Statisticians have a...
One of the most straightforward examples of how we use Bayes to update our beliefs as we acquire more information can be seen with a simple Bernoulli process. That is, a process which has only two possible outcomes. Probably the most commonly thought of example is that of a coin toss. The outcome of...
Check them out. Here are thirty homoskedastic ones: > homo.wiener for (j in 1:30) { for (i in 2:length(homo.wiener)) { homo.wiener for (j in 1:30) { plot( homo.wiener, type = "l", col = rgb(.1,....
One of my teaching roles is in an introductory Genetics course, where first year students are presented with a wide range of new ideas at a relatively fast pace. It seems that often, students choose to take a memorization approach to learning the material, rather than taking the chance to think about how and...
We often simulate data in SAS or R to confirm analytical results. For example, consider the following problem from the excellent text by Rice:Let U1, U2, and U3 be independent random variables uniform on . What is the probability that the roots...
Today, at lunch, Matthieu told us a nice story (or call it a paradox if you like) about the probability to find you seat empty when you get in a place. a plane full of nuns Assume that you are in the line to get in the airplane, you are the ...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).