Via Zenpencils Go placidly amid the noise and haste, and remember what peace there may be in silence. As far as possible, without surrender, be on good terms with all persons. Speak your truth quietly and clearly; and listen to others, even to the dull and the ignorant, they too have their story. Avoid loud and aggressive persons, they are vexations to the spirit. If you compare yourself with others, you may become vain and bitter; for always there will be greater and lesser persons than yourself.

When physicists do mathematics, they don’t say they’re doing “number science”. They’re doing math. If you’re analyzing data, you’re doing statistics. You can call it data science or informatics or analytics or whatever, but it’s still statistics. - Karl Broman

I was looking to code Metropolis-within-Gibbs sampler for a specific model and in that process, stumbled on to an online supplement for a work-in-progress book,``Handbook of Modern Item Response Theory''. The following document summarizes the main points from chapter-15 of the book. The document also contains WinBUGS code to estimate the parameters of 2PL model. Building Metropolis Hastings sampler from scratch

“You never quit on your music. No matter what happens. Cuz anytime something bad happens to you, that’s the one place you can escape to and just let it go. I learned it the hard way” - August Rush

Modeling Capture-Recapture Data via Bayes involves specifying the likelihood of the survival + encounter probabilities and the priors on the parameters. A natural extension of a plain vanilla model is to make the survival probabilities time dependent. The paper titled, “Autoregressive models for capture–recapture data: A Bayesian approach”, is about modeling the survival probabilities by taking various covariates such as time and random effects. The following document contains a brief summary of the paper :