PDF of (X, X)

The PDF of (X, X) does not exist… in the ordinary sense

September 29, 2024 · 4 min · Pantelis Sopasakis

Estimation Crash Course IV: Sufficient Statistics

Sufficient statistics

August 31, 2023 · 4 min · Pantelis Sopasakis

Estimation Crash Course III: Cramér-Rao bound

The Cramér-Rao Bound is a lower bound on the variance of an unbiased estimator. Here we focus on one-parameter models.

August 29, 2023 · 4 min · Pantelis Sopasakis

Estimation Crash Course II: Fisher information

Introduction of the notion of Fisher information: a quantity of central importance in statistics.

August 23, 2023 · 8 min · Pantelis Sopasakis

Estimation Crash Course I: Statistics and Estimators

Statistics and Estimators: definitions of statisics and an introduction to the concepts of bias and variance of an estimator; several examples.

August 20, 2023 · 6 min · Pantelis Sopasakis

Reading Vershynin's HDP II: Subgaussianity

We study the class of sub-Gaussian random variables: those random variables whose tails are dominated by a Gaussian. Such random variables satisfy Hoeffding-type bounds and possess several interesting properties. We also define the sub-Gaussian norm and study its properties.

June 29, 2023 · 13 min · Pantelis Sopasakis

Reading Vershynin's HDP I: Markov, Chernoff, Hoeffding

A result on the convergence of sample mean and notes on some standard concentration inequalities such as the Markov, Chernoff, Hoeffding, and Chernoff’s bounds

June 28, 2023 · 10 min · Pantelis Sopasakis

The Kalman Filter II: Conditioning

We derive a useful formula that allows us to compute the conditional expectation of jointly normally distributed data; this result plays a central role in the development of the Kalman filter

February 1, 2023 · 3 min · Pantelis Sopasakis

Polynomial chaos expansions: Part I

An introduction to polynomial chaos expansions

September 6, 2022 · 9 min · Pantelis Sopasakis

Probability cookbook

Probability cookbook

August 18, 2022 · 1 min · Pantelis Sopasakis