After reading data, making a predictions display and building a football data model it is time to put this to validate a bit more (regression plots) and put to usage. It appears that the regression plots in the car package were not ...

It’s been quite a while since my last post on Euler problems. Today a visitor post his solution to the second problem nicely, which encouraged me to keep solving these problems. Just for fun! 10! = 10 * 9 * … * 3 * 2 * 1 … Continue reading →

Numerically-coded data sequences can exhibit a very wide range of distributional characteristics, including near-Gaussian (historically, the most popular working assumption), strongly asymmetric, light- or heavy-tailed, multi-modal, or discrete (e.g., count data). In addition, numerically coded values can be effectively categorical, either ordered, or unordered. A specific example that illustrates the range of distributional behavior often seen in a collection...

Consider our loss-ALAE dataset, and – as in Frees & Valdez (1998) - let us fit a parametric model, in order to price a reinsurance treaty. The dataset is the following, > library(evd) > data(lossalae) > Z=lossalae > X=Z;Y=Z The first step can be to estimate marginal distributions, independently. Here, we consider lognormal distributions for both components, > Fempx=function(x) mean(X<=x) >...

I write sloppy R scripts. It is a byproduct of working with a high-level language that allows you to quickly write functional code on the fly (see this post for a nice description of the problem in Python code) and the result of my limited formal training in computer programming. The lack of formal training

This post is actually a homework I did. The data file contains input use, output, quantities, costs, and prices for total U.S. nondurable manufacturing for 1949-2001. The data are deﬁned as follows: , , , , = Inputs corresponding to capital, labor, energy, materials, and purchased services, = represents total output, = respective quantity indexes, ...

Another full day spent working with Jean-Michel Marin on the new edition of Bayesian Core (soon to be Bayesian Essentials with R!) and the remaining hierarchical Bayes chapter… I have reread and completed the regression and GLM chapters, sent to very friendly colleagues for a last round of comments. Now, I am essentially idle, waiting