Use of mean residual life in testing departures from exponentiality

Jammalamadaka, S. Rao; Taufer, Emanuele

doi:10.1080/10485250600759454

Cited by 15 publications

(10 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Tests based on the MRL (and the various forms of the characterising properties given in (9) to (11)) to test for exponentiality can be found in Baringhaus and Henze (2000), Jammalamadaka and Taufer (2006), and Taufer (2000). A generalisation of the test in Baringhaus and Henze (2000) which includes a more general weight function can be found in Baringhaus and Henze (2008).…”

Section: Tests Based On Mean Residual Lifementioning

confidence: 99%

“…A generalisation of the test in Baringhaus and Henze (2000) which includes a more general weight function can be found in Baringhaus and Henze (2008). The two tests considered in this paper, namely the Jammalamadaka and Taufer test from Jammalamadaka and Taufer (2006) and the Baringhaus and Henze test from Baringhaus and Henze (2000), employ the characterisations in (9) and (10), respectively. The test proposed by Taufer in Taufer (2000), however, makes use of the characterisation in (11).…”

Section: Tests Based On Mean Residual Lifementioning

confidence: 99%

“…However, the most recent review paper on this topic was written more than 10 years ago by Henze and Meintanis (2005). Since then, a number of new tests have been proposed, see for example Jammalamadaka and Taufer (2006), Haywood and Khmaladze (2008), Mimoto and Zitikus (2008), Wang (2008), Volkova (2010), Grané and Fortiana (2011), Abbasnejad et al (2012), Baratpour and Habibi Rad (2012), Volkova and Nikitin (2013), Meintanis et al (2014), and Zardasht et al (2015). Furthermore, many of the tests for exponentiality contain a tuning parameter, often appearing in a weight function.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2017

View full text Add to dashboard Cite

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.

show abstract

Section: Tests Based On Mean Residual Lifementioning

confidence: 99%

Section: Tests Based On Mean Residual Lifementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2017

View full text Add to dashboard Cite

show abstract

“…In the complete sample case, numerous tests for testing the hypothesis that the observed data are realizations from the exponential distribution have been developed and studied. These include tests based on characteristic functions (Epps & Pulley, ; Meintanis, Swanepoel, & Allison, ), Laplace transforms (Baringhaus & Henze, ; Henze & Meintanis, ), mean residual life (Baringhaus & Henze, ; Jammalamadaka & Taufer, ), normalized spacings (Gnedenko, Belyayev, & Solovyev, ), and entropy (Zardasht, Parsi, & Mousazadeh, ; Baratpour & Rad, ) to name just a few. Furthermore, there are a multitude of properties that characterize the exponential distribution, see, for example, the monographs of Galambos and Kotz () and Kotz, Balakrishnan, and Johnson ().…”

Section: Introductionmentioning

confidence: 99%

Modified tests for exponentiality in the presence of Type II right censored data

Cockeran

Santana

Allison

2019

Stat

View full text Add to dashboard Cite

The exponential distribution is one of the most popular choices of model, especially in survival analysis and reliability theory. Typically, to test the hypothesis that the underlying distribution of lifetimes are exponentially distributed based on censored data, the standard goodness‐of‐fit tests used in the complete sample case are modified. However, none of the characteristic or Laplace function based tests have been adapted to incorporate censored data. In this paper, we modify three well‐known tests for exponentiality on the basis of either the characteristic function or Laplace transform to accommodate Type II right censored data. We compare the power of the three newly changed tests to some existing modified tests in an independent identically distributed (i.i.d.) and a model‐based setup through a Monte Carlo study, where it was found that the newly adjusted Baringhaus and Henze test outperformed all other tests considered.

show abstract

“…Among them many tests are based on characterizations of exponential law, in particular on loss-of-memory property ( [1], [4], [20], [21], [25]) and some other characterizations ( [9], [16], [22], [30], [31], [32], [33]). The construction of tests based on characterizations is a relatively fresh idea which gradually becomes one of main directions in goodness-of-fit testing.…”

Section: Introductionmentioning

confidence: 99%

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

Jovanović

Milošević

Nikitin

et al. 2015

Computational Statistics & Data Analysis

View full text Add to dashboard Cite

Abstract. We propose two families of scale-free exponentiality tests based on the recent characterization of exponentiality by Arnold and Villasenor. The test statistics are based on suitable functionals of U -empirical distribution functions. The family of integral statistics can be reduced to V -or U -statistics with relatively simple non-degenerate kernels. They are asymptotically normal and have reasonably high local Bahadur efficiency under common alternatives.This efficiency is compared with simulated powers of new tests. On the other hand, the Kolmogorov type tests demonstrate very low local Bahadur efficiency and rather moderate power for common alternatives, and can hardly be recommended to practitioners. We also explore the conditions of local asymptotic optimality of new tests and describe for both families special "most favorable" alternatives for which the tests are fully efficient.

show abstract

Use of mean residual life in testing departures from exponentiality

Cited by 15 publications

References 28 publications

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

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

Modified tests for exponentiality in the presence of Type II right censored data

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

Contact Info

Product

Resources

About