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Found 6 papers, 0 papers with code
Bayesian Consistency with the Supremum Metric
We present simple conditions for Bayesian consistency in the supremum metric.
On Integral Theorems and their Statistical Properties
We introduce a class of integral theorems based on cyclic functions and Riemann sums approximating integrals.
Statistical Analysis from the Fourier Integral Theorem
Taking the Fourier integral theorem as our starting point, in this paper we focus on natural Monte Carlo and fully nonparametric estimators of multivariate distributions and conditional distribution functions.
A Reinforcement Learning Based Approach to Play Calling in Football
With the vast amount of data collected on football and the growth of computing abilities, many games involving decision choices can be optimized.
Multivariate Smoothing via the Fourier Integral Theorem and Fourier Kernel
Starting with the Fourier integral theorem, we present natural Monte Carlo estimators of multivariate functions including densities, mixing densities, transition densities, regression functions, and the search for modes of multivariate density functions (modal regression).
Testing to distinguish measures on metric spaces
We study the problem of distinguishing between two distributions on a metric space; i. e., given metric measure spaces $({\mathbb X}, d, \mu_1)$ and $({\mathbb X}, d, \mu_2)$, we are interested in the problem of determining from finite data whether or not $\mu_1$ is $\mu_2$.
