distracting redistricting?

“We at FiveThirtyEight will be tracking the whole redistricting process, from proposed maps to final maps, so watch this space for updates!”

FiveThirtyEight is keeping a tracker on the “redistricting” of U.S. states, namely the decennial redrawing of electoral districts. This is still an early stage when no map has been validated by the state legislature and hence I cannot tell whether or not FiveThirtyEight will be analysing gerrymandering in a statistical manner, to figure out how extreme the map is within the collection of all electoral maps. The States being the States, the rules vary widely between them, from the legislators themselves setting the boundaries (while sometimes being very open on their intentions to favour their own side) to independent commissions being in charge. I did not spot any clear involvement of statisticians in the process.

“The application of differential privacy will bring significant harm to Alabama (…) The Census Bureau has not shown that other disclosure avoidance methods
would not satisfy the privacy requirements” Case No. 3:21-cv-00211

While looking at this highly informative webpage maintained by University of Colorado Law School Doug Spencer, I came across this federal court challenge by the State of Alabama again the Census Bureau for using differential privacy! A statistical version of “shoot the messenger”?! The legal argument of the State is “the Fifth Amendment, alleging that differential privacy is a violation of the one-person, one-vote principle and will result in the dilution of their votes.” I however wonder what is the genuine (political) reason for this challenge!

mixtures, Heremite polynomials, and ideals

A 3 page note that got arXived today is [University of Colorado?!] Andrew Clark’s “Expanding the Computation of Mixture Models by the use of Hermite Polynomials and Ideals“. With a typo on Hermite‘s name in the pdf title. The whole point of the note is to demonstrate that mixtures of different types of distributions (like t and Gaussian) are manageable.  A truly stupendous result… As if no one had ever mixed different distributions before.

“Using Hermite polynomials and computing ideals allows the investigator to mix distributions from distinct families.”

The second point of the paper is to derive the mixture weights from an algebraic equation based on the Hermite polynomials of the components, which implies that the components and the mixture distribution itself are already known. Which thus does not seem particularly relevant for mixture estimation…