arXiv subjects

Calvin Wooyoung Chin

Publications and source records attributed to Calvin Wooyoung Chin.

6 recordsLinked to original sources

arXiv2024

A Proof of the Central Limit Theorem Using the $2$-Wasserstein Metric

We prove the Lindeberg--Feller central limit theorem without using characteristic functions or Taylor expansions, but instead by measuring how far a distribution is from the standard normal distribution according to the $2$-Wasserstein metric. This falls under the category of renormalization group methods. The facts we need about the metric are explained and proved in detail. We illustrate the idea on a classical version of the central limit theorem before going into the main proof.

math.PR↗

arXiv2022

Necessary and Sufficient Conditions for Convergence to the Semicircle Distribution

We consider random Hermitian matrices with independent upper triangular entries. Wigner's semicircle law says that under certain additional assumptions, the empirical spectral distribution converges to the semicircle distribution. We characterize convergence to semicircle in terms of the variances of the entries, under natural assumptions such as the Lindeberg condition. The result extends to certain matrices with entries having infinite second moments. As a corollary, another characterization of semicircle convergence is given in terms of convergence in distribution of the row sums to the standard normal distribution.

math.PR↗

arXiv2022

A Mass Transport Proof of the Ergodic Theorem

It is known that a gambler repeating a game with positive expected value has a positive probability to never go broke. We use the mass transport method to prove the generalization of this fact where the gains from the bets form a stationary, rather than an i.i.d., sequence. Birkhoff's ergodic theorem follows from this by a standard argument.

math.PR↗

arXiv2021

Deriving the Central Limit Theorem from the De Moivre-Laplace Theorem

The de Moivre-Laplace theorem is a special case of the central limit theorem for Bernoulli random variables, and can be proved by direct computation. We deduce the central limit theorem for any random variable with finite variance from the de Moivre-Laplace theorem. Our proof does not use advanced notions such as characteristic functions, the Brownian motion, or stopping times.

math.PR↗

arXiv2021

A Short and Elementary Proof of the Central Limit Theorem by Individual Swapping

We present a short proof of the central limit theorem which is elementary in the sense that no knowledge of characteristic functions, linear operators, or other advanced results are needed. Our proof is based on Lindeberg's trick of swapping a term for a normal random variable in turn. The modifications needed to prove the stronger Lindeberg-Feller central limit theorem are addressed at the end.

math.PR↗

arXiv2021

A Gambler that Bets Forever and the Strong Law of Large Numbers

In this expository note, we give a simple proof that a gambler repeating a game with positive expected value never goes broke with a positive probability. This does not immediately follow from the strong law of large numbers or other basic facts on random walks. Using this result, we provide an elementary proof of the strong law of large numbers. The ideas of the proofs come from the maximal ergodic theorem and Birkhoff's ergodic theorem.

math.PR↗