Work

Normality tests: a study of residuals obtained on time series tendency modeling

Year: 2023

Type: article

Abstract: The normality analysis in the distribution of residuals is a determining criterion to verify and validate a model. For example, in modeling financial time series by linear regression, the residuals should be independent of each other, identically distributed, have a normal distribution, and be homoscedastic. Thus, it was aimed to study the performance of some normality tests applied on the residuals obtained from linear regression modeling of time series tendency using polynomials of different degrees. The Jarque-Bera, Anderson-Darling, Kolmogorov-Smirnov-Lilliefors, Doornik-Hansen, and Shapiro-Wilk tests were used, there was agreement in almost all test results, with the exception of the Doornik-Hansen test.

Source: Exacta

DOI: 10.5585/2023.22928

Authors: Fabian Corrêa Cardoso, Rafael Alceste Berri, Giancarlo Lucca, Eduardo Nunes Borges, Viviane Leite Dias de Mattos

Institution: Universidade Federal do Rio Grande

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: diamond

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul

Award: G6794256107