Statistical inference for piecewise normal distributions and stochastic variational inequalities

07/11/2019
by   Shu Lu, et al.
0

In this paper we first provide a method to compute confidence intervals for the center of a piecewise normal distribution given a sample from this distribution, under certain assumptions. We then extend this method to an asymptotic setting, and apply this method to compute confidence intervals for the true solution of a stochastic variational inequality based on a solution to a sample average approximation problem. The confidence intervals are computed with simple formulas. Performance of the proposed method is tested with numerical experiments.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/17/2018

Confidence Intervals for Testing Disparate Impact in Fair Learning

We provide the asymptotic distribution of the major indexes used in the ...
research
12/29/2020

Statistical Formulas for F Measures

We provide analytic formulas for the standard error and confidence inter...
research
12/04/2020

MCMC Confidence Intervals and Biases

The recent paper "Simple confidence intervals for MCMC without CLTs" by ...
research
09/26/2020

Constructing Confidence Intervals for the Signals in Sparse Phase Retrieval

In this paper, we provide a general methodology to draw statistical infe...
research
02/10/2020

Likelihood, Replicability and Robbins' Confidence Sequences

The widely claimed replicability crisis in science may lead to revised s...
research
12/12/2021

Approximation algorithms for confidence bands for time series

Confidence intervals are a standard technique for analyzing data. When a...

Please sign up or login with your details

Forgot password? Click here to reset