A Kolmogorov-Smirnov type test for two inter-dependent random variables

02/27/2018
by   Tommy Liu, et al.
0

Consider n iid random variables, where ξ_1, ..., ξ_n are n realisations of a random variable ξ and ζ_1, ..., ζ_n are n realisations of a random variable ζ. The distribution of each realisation of ξ, that is the distribution of one ξ_i, depends on the value of the corresponding ζ_i, that is the probability P(ξ_i≤ x)=F(x,ζ_i). We develop a statistical test to see if the ξ_1, ..., ξ_n are distributed according to the distribution function F(x,ζ_i). We call this new statistical test the condition Kolmogorov-Smirnov test.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/25/2023

Statistical Depth Function Random Variables for Univariate Distributions and induced Divergences

In this paper, we show that the halfspace depth random variable for samp...
research
03/25/2019

The Random Conditional Distribution for Higher-Order Probabilistic Inference

The need to condition distributional properties such as expectation, var...
research
03/02/2018

On some discrete random variables arising from recent study on statistical analysis of compressive sensing

The recent paper [27] provides a statistical analysis for efficient dete...
research
12/31/2017

Benford's Law Beyond Independence: Tracking Benford Behavior in Copula Models

Benford's law describes a common phenomenon among many naturally occurri...
research
07/08/2021

How to measure things

In classical information theory, a causal relationship between two rando...
research
03/15/2022

Comparing two samples through stochastic dominance: a graphical approach

Non-deterministic measurements are common in real-world scenarios: the p...
research
09/21/2020

Multi-Gaussian random variables

A generalization of the classic Gaussian random variable to the family o...

Please sign up or login with your details

Forgot password? Click here to reset