Detection of non-Gaussianity
From MaRDI portal
Publication:5222300
DOI10.1080/00949655.2014.983110OpenAlexW2066910950MaRDI QIDQ5222300
Grzegorz Wyłupek, Teresa Ledwina
Publication date: 1 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://figshare.com/articles/journal_contribution/Detection_of_non_Gaussianity/1250828
model selectiongoodness-of-fitWasserstein distancehigher criticism\(L\)-statisticcorrelation testShapiro-Wilk testtest of normalitysample quantile functionAkaike selection rule
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Weighted correlation tests for location-scale families
- A study of the quantile correlation test for normality
- Data. A collection of problems from many fields for the student and research worker
- Optimal goodness-of-fit tests for location-scale families of distributions based on the sum of squares of L-statistics
- Cramér-von Mises statistics based on the sample quantile function and estimated parameters
- Optimal goodness-of-fit tests for normality against skewness and kurtosis alternatives
- The asymptotic distribution of the supremum of the standardized empirical distribution function on subintervals
- The asymptotic distribution of the suprema of the standardized empirical processes
- Tests of goodness of fit based on the \(L_2\)-Wasserstein distance
- Intermediate approach to comparison of some goodness-of-fit tests
- Goodness-of-fit tests for location and scale families based on a weighted \(L_ 2\)-Wasserstein distance measure.
- Weighted \(W\) test for normality and asymptotics a revisit of Chen--Shapiro test for normality
- Higher criticism for detecting sparse heterogeneous mixtures.
- Cosmological non-Gaussian signature detection: comparing performance of different statistical tests
- Do financial returns have finite or infinite variance? A paradox and an explanation
- Optimal Detection of Heterogeneous and Heteroscedastic Mixtures
- On netman-type smooth tests of fit
- An empirical power comparison of univariate goodness-of-fit tests for normality
- Quadratic nuisance-parameter-free goodness-of-fit tests in the presence of location and scale parameters
- Goodness-of-Fit Tests Based on Nonlinearity in Probability Plots
- Data-Driven Version of Neyman's Smooth Test of Fit
- An alernative test for normality based on normalized spacings
- Normal Scores, Normal Plots, and Tests for Normality
- An analysis of variance test for normality (complete samples)
- Understanding some long‐tailed symmetrical distributions
This page was built for publication: Detection of non-Gaussianity