![twilight zone [of statistics]](https://xianblog.files.wordpress.com/2016/02/mix2means.jpg?w=400&h=400)
“I have decided that mixtures, like tequila, are inherently evil and should be avoided at all costs.” L. Wasserman Larry Wasserman once remarked that finite mixtures were like the twilight zone of statistics, thanks to the numerous idiosyncrasies associated with such models. And George Casella had similar strong reservations about mixture estimation. Avi Feller and […]
“…for a general linear model (GLM), a single linear function is a sufficient statistic for each associated parameter…” The recently arXived paper “Likelihood-free inference in high-dimensional models“, by Kousathanas et al. (July 2015), proposes an ABC resolution of the dimensionality curse [when the dimension of the parameter and of the corresponding summary statistics] by turning […]
“…for a general linear model (GLM), a single linear function is a sufficient statistic for each associated parameter…” The recently arXived paper “Likelihood-free inference in high-dimensional models“, by Kousathanas et al. (July 2015), proposes an ABC resolution of the dimensionality curse [when the dimension of the parameter and of the corresponding summary statistics] by turning […]
Luke Bornn, Neil Shephard, and Reza Solgi (all from Harvard) have arXived a pretty interesting paper on simulating targets on a zero measure set. Although it is not initially presented this way, but rather in non-parametric terms as moment conditions where θ is the parameter of the sampling distribution, constrained by the value of β. (Which […]
“…our findings shall lead to us be critical of certain current practices. Specifically, most papers seem content with comparing some new algorithm with Gibbs sampling, on a few small datasets, such as the well-known Pima Indians diabetes dataset (8 covariates). But we shall see that, for such datasets, approaches that are even more basic than […]
On Cross Validated, I had a rather extended discussion with a user about a probability density as I thought it could be decomposed in two manageable conditionals and simulated by Gibbs sampling. The first component led to a Gumbel like density wirh y being restricted to either (0,1) or (1,∞) depending on β. The density […]
In a cross-validated forum exchange, I used the code below to illustrate the working of an ABC algorithm: Hence I used the median and the mad as my summary statistics. And the outcome is rather surprising, for two reasons: the first one is that the posterior on the mean μ is much wider than […]
Following yesterday’s post on Rao’s, Liu’s, and Dunson’s paper on a new approach to intractable normalising constants, and taking advantage of being in Warwick, I tested the method on a toy model, namely the posterior associated with n Student’s t observations with unknown location parameter μ and a flat prior, which is “naturally” bounded by […]
![fine-sliced Poisson [a.k.a. sashimi]](http://xianblog.files.wordpress.com/2014/03/slisson2.jpg?w=450&h=450)
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 […]
