Yesterday, I did upload a post where I tried to show that “standard” regression models where not performing bad. At least if you include splines (multivariate splines) to take into accound joint effects, and nonlinearities. So far, I do not discuss the possible high number of features (but with boostrap procedures, it is possible to assess something related to variable importance, that people from machine learning like). But my post…
When you start discussing with people in machine learning, you quickly hear something like “forget your econometric models, your GLMs, I can easily find a machine learning ‘model’ that can beat yours”. I am usually very sceptical, especially when I hear “easily” or “always“. I have no problem about the fact that I use old econometric models, but I had the feeling that things aren’t that easy. I can understand…
One of the attractive aspects of logistic regression models (and linear models in general) is their compactness: the size of the model grows in the number of coefficients, not in the size of the training data. With R, though, glm models are not so concise; we noticed this to our dismay when we tried to […] Related posts: Generalized linear models for predicting rates Bad Bayes: an example of why…
I often need to build a predictive model that estimates rates. The example of our age is: ad click through rates (how often a viewer clicks on an ad estimated as a function of the features of the ad and the viewer). Another timely example is estimating default rates of mortgages or credit cards. You […] Related posts: What does a generalized linear model do? The equivalence of logistic regression…
Most of the time, when we introduce binomial models, such as the logistic or probit models, we discuss only Bernoulli variables, . This year (actually also the year before), I discuss extensions to multinomial regressions, where is a function on some simplex. The multinomial logistic model was mention here. The idea is to consider, for instance with three possible classes the following model and Now, what about a real Binomial model, , where ‘s are known. How…
Tomorrow, around noon, I will be giving a talk on predictive modeling for actuaries. In the introduction, I will get back shortly on the idea that a prediction is usually a best estimate, in the sense of getting an expected value. And because it is natural to use least square ideas. In order to illustrate all those concepts, we will use a simple dataset, with the sex, the height and…
Dans un modèle de régression, on veut écrire Quand on se limite à un modèle linéaire, on écrit Mais on de doute que l’on rate quelque chose… en particulier, on va rater toutes les interactions possibles. On peut croiser les variables, et supposer que qui peut s’étendre d’avantage, à l’ordre 3, voire davantage. Supposons que nos variables soient ici qualitatives, et plus précisément binaires. Prenons un exemple simple, avec des données…
This morning, I was working with Julie, a student of mine, coming from Rennes, on mortality tables. Actually, we work on genealogical datasets from a small region in Québec, and we can observe a lot of volatiliy. If I borrow one of her graph, we get something like Since we have some missing data, we wanted to use some Generalized Nonlinear Models. So let us see how to get a…
I will give, with Qichun Xu, a joint webinar for the Reinsurance Council and the Futurism Council of the Society of Actuaries, on Perspectives of Predictive Modeling with Case Studies in a few days. The slides of my talk are now available (I do recommand to open the pdf version of the slides with Acrobat, since there are animated pictures in the slides that could not be visualized below for instance).…
Following my non-life insurance class, this morning, I had an interesting question from a student, that I will try to illustrate, and reformulate as accurately as possible. Consider a simple regression model, with one variable of interest, and one possible explanatory variable. Assume that we have two possible models, with the following output (yes, I do hide interesting parts here, but it is to get quickly to my student’s point)…
