Tests of exponentiality based on Arnold–Villasenor characterization and their efficiencies

Jovanović, Miodrag; Milošević, Bojana; Nikitin, Ya. Yu.; Obradović, M; Volkova, K. Yu.

doi:10.1016/j.csda.2015.03.019

Cited by 26 publications

(18 citation statements)

References 35 publications

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“…Over the years, a multitude of tests for exponentiality have been developed by utilising a number of interesting and varied characterisations and properties of the exponential distribution, but it would not be possible to address all of them in a single study. These tests utilise characterisations such as the memoryless property (see, for example, Ahmad and Alwasel, 1999;Alwasel, 2001;Angus, 1982), the Arnold-Villasenor characterisation (see Jovanović et al, 2015), the Rossberg characterisation (Volkova, 2010), and various other characterisations (see, for example, Abbasnejad et al, 2012;Noughabi and Arghami, 2011a). Other tests for exponentiality, not included in this paper, include tests for exponentiality based on the analysis of variance (see Shapiro and Wilk, 1972), tests based on order statistics (see Bartholomew, 1957;Hahn and Shapiro, 1967;Jackson, 1967;Wong and Wong, 1979), tests based on transformations to uniformity (see Hegazy and Green, 1975;Seshadri et al, 1969), and tests based on maximum correlations (see Grané and Fortiana, 2011), to name but a few.…”

Section: Tests Based On Other Characterizations and Propertiesmentioning

confidence: 99%

An ‘apples to apples’ comparison of various tests for exponentiality

et al. 2017

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The exponential distribution is a popular model both in practice and in theoretical work. As a result, a multitude of tests based on varied characterisations have been developed for testing the hypothesis that observed data are realised from this distribution. Many of the recently developed tests contain a tuning parameter, usually appearing in a weight function. In this paper we compare the powers of 20 tests for exponentiality-some containing a tuning parameter and some that do not. To ensure a fair 'apples to apples' comparison between each of the tests, we employ a data-dependent choice of the tuning parameter for those tests that contain these parameters. The comparisons are conducted for various samples sizes and for a large number of alternative distributions. The results of the simulation study show that the test with the best overall power performance is the Baringhaus & Henze test, followed closely by the test by Henze & Meintanis; both tests contain a tuning parameter. The score test by Cox & Oakes performs the best among those tests that do not include a tuning parameter.

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Section: Tests Based On Other Characterizations and Propertiesmentioning

confidence: 99%

An ‘apples to apples’ comparison of various tests for exponentiality

et al. 2017

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“…For example, for tests based on the mean residual life, see [8], [25], [17], and [9]. For a test based on the Arnold-Villasenor characterisation, see [18], and for a test based on the Rossberg characterisation see [27]. For a comprehensive review of tests for exponentiality, the interested reader is referred to the review papers by Ascher [7], Henze and Meintanis [16], and Allison, Santana, Smit and Visagie [4].…”

Section: Introductionmentioning

confidence: 99%

New goodness-of-fit test for exponentiality based on a conditional moment characterisation

Smuts

Allison

Santana

2019

ORiON

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The exponential distribution plays a key role in the practical application of reliability theory, survival analysis, engineering and queuing theory. These applications often rely on the underlying assumption that the observed data originate from an exponential distribution. In this paper, two new tests for exponentiality are proposed, which are based on a conditional second moment characterisation. The proposed tests are compared to various established tests for exponentiality by means of a simulation study where it is found that the new tests perform favourably relative to the existing tests. The tests are also applied to real-world data sets with independent and identically distributed data as well as to simulated data from a Cox proportional hazards model, to determine whether the residuals obtained from the fitted model follow a standard exponential distribution.

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“…Later Yanev and Chakraborty [105] proved that it is true for k = 3, and later in [106] proved it for arbitrary k (see also [61]). Tests of exponentiality based on these characterizations and their efficiencies were studied in [35] and in [100].…”

Section: Characterization Of Arnold and Villaseñor Recently Arnold Andmentioning

confidence: 99%

Tests based on characterizations, and their efficiencies: a survey

Nikitin

2017

ACUTM

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Abstract. A survey of goodness-of-fit and symmetry tests based on the characterization properties of distributions is presented. This approach became popular in recent years. In most cases the test statistics are functionals of U -empirical processes. The limiting distributions and large deviations of new statistics under the null hypothesis are described. Their local Bahadur efficiency for various parametric alternatives is calculated and compared with each other as well as with diverse previously known tests. We also describe new directions of possible research in this domain.

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Tests of exponentiality based on Arnold–Villasenor characterization and their efficiencies

Cited by 26 publications

References 35 publications

An ‘apples to apples’ comparison of various tests for exponentiality

An ‘apples to apples’ comparison of various tests for exponentiality

New goodness-of-fit test for exponentiality based on a conditional moment characterisation

Tests based on characterizations, and their efficiencies: a survey

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