Weighted Kolmogrov–Smirnov type tests for grouped Rayleigh data

Baklizi, Ayman

doi:10.1016/j.apm.2005.05.012

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…Recently, Sultan (2001) has devolved the correlation goodness-of-fit to the logarithmically-decreasing survival distribution. Baklizi (2006) has suggested weighted Kolmogrove-Smirnov type test for grouped Rayleigh data. Chen (2006) has discussed some tests of fit for the three-parameter lognormal distribution.…”

Section: ð1:1þmentioning

confidence: 99%

Discriminating between gamma and lognormal distributions with applications

Alzaid

2009

Journal of King Saud University - Science

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In this paper, we discuss the use of the coefficient of skewness as a goodness-of-fit test to distinguish between the gamma and lognormal distributions. We also show the limitations of this idea. Next, we use the moments of order statistics from gamma distribution to adjust the correlation goodness-of-fit test. In addition, we calculate the power of the test based on some other alterative distributions including the lognormal distribution. Further, we show some numerical illustration. Finally, we apply the procedure developed in the paper to some real data sets.

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Section: ð1:1þmentioning

confidence: 99%

Discriminating between gamma and lognormal distributions with applications

Alzaid

2009

Journal of King Saud University - Science

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“…The initial statistic for goodness of fit test is CH square, then other statistics are considered as a distance between the theoretical and empirical distribution, for details see ref [10]. Test statistics are derived from the sum of discrepancies between the empirical and the hypothetical distribution functions.…”

Section: Introductionmentioning

confidence: 99%

“…Spinelli [9] has considered these statistics for testing grouped data fit to the exponential distribution. Baklizi [10] proposed the weighted Kolmogorov test statistics for the Rayleigh interval grouped data. Many other researchers studied the asymptotic distributions of some of these statistics as in Schmid [11] and Pettitt and Stephens [12].…”

Section: Introductionmentioning

confidence: 99%

On the Power Performance of Test Statistics for the Generalized Rayleigh Interval Grouped Data

Migdadi

2015

OJS

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In this paper, the weighted Kolmogrov-Smirnov, Cramer von-Miss and the Anderson Darling test statistics are considered as goodness of fit tests for the generalized Rayleigh interval grouped data. An extensive simulation process is conducted to evaluate their controlling of type 1 error and their power functions. Generally, the weighted Kolmogrov-Smirnov test statistics show a relatively better performance than both, the Cramer von-Miss and the Anderson Darling test statistics. For large sample values, the Anderson Darling test statistics cannot control type 1 error but for relatively small sample values it indicates a better performance than the Cramer von-Miss test statistics. Best selection of the test statistics and highlights for future studies are also explored.

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