Traffic characteristics of aggregated module downloads for mobile terminal reconfiguration

Holland, Oliver; Golaup, A.; Aghvami, A.H.

doi:10.1049/ip-com:20045155

Cited by 39 publications

(36 citation statements)

References 6 publications

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“…So, focusing on the point estimates of  in these first two cases, bias-adjusting the MLEs induces an important change to the characteristics of the Lomax distribution, even though the numerical differences may not seem large. Interestingly, the values of  and ˆ associated with computer file data are very similar to those obtained by Holland et al (2006) . They did not report standard errors, and of course, they did not bias-adjust their estimates.…”

Section: Illustrative Applicationssupporting

confidence: 70%

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On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution

Giles

Feng

Godwin

2013

Communications in Statistics - Theory and Methods

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The Lomax (Pareto II) distribution has found wide application in a variety of fields. We analyze the second-order bias of the maximum likelihood estimators of its parameters for finite sample sizes, and show that this bias is positive. We derive an analytic bias correction which reduces the percentage bias of these estimators by one or two orders of magnitude, while simultaneously reducing relative mean squared error. Our simulations show that this analytic bias correction outperforms a correction based on the parametric bootstrap. Three examples with actual data illustrate the application of our methods.

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Section: Illustrative Applicationssupporting

confidence: 70%

“…It has also found application in the biological sciences and even for modelling the distribution of the sizes of computer files on servers (Holland et al, 2006). Some authors, such as Bryson (1974), have suggested the use of this distribution as an alternative to the exponential distribution when the data are heavy-tailed.…”

Section: Introductionmentioning

confidence: 99%

On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution

Giles

Feng

Godwin

2013

Communications in Statistics - Theory and Methods

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“…Hence, in the window (8,12], we may have a regime switching, which could be either a drop or a jump depending on the sign of . Specifically, when = −0.5, the transfer function has a sudden drop at the point x 0 = 10, and when = 0.5, it has a sudden jump at the point.…”

Section: Transfer Functionmentioning

confidence: 99%

Assessing Transfer Functions in Control Systems

Gribkova

Zitikis

2019

J Stat Theory Pract

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When dealing with control systems, it is useful and even necessary to assess the performance of underlying transfer functions. The functions may or may not be linear, may or may not be even monotonic. In addition, they may have structural breaks and other abberations that require monitoring and quantification to aid decision making. The present paper develops such a methodology, which is based on an index of increase that naturally arises as the solution to an optimization problem. We show theoretically and illustrate numerically that the empirical counterpart of the index needs to be used with great care and indepth knowledge of the problem at hand in order to achieve desired large-sample properties, such as consistency.

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“…This distribution has found wide applications such as the analysis of the business failure life time data, income and wealth inequality, size of cities, actuarial science, medical and biological sciences, engineering, lifetime and reliability modeling. Furthermore, it has been applied to model data obtained from income and wealth by Harris [17] and Atkinson et al [5], firm size by Corbellini et al [10], size distribution of computer files on servers by Hollanh et al [19], reliability and life testing by Hassan et al [18], receiver operating characteristic (ROC) curve analysis by Campbell et al [9] and Hirsch-related statistics by Glanzel [15]. In the lifetime, the Lomax model belongs to the family of decreasing failure rate by Chahkandi et al [11] and arises as a limiting distribution of residual lifetimes at great age by Balkema et al [7].…”

Section: Introductionmentioning

confidence: 99%

Exponential Lomax Distribution

El-Bassiouny¹,

Abdo²,

Shahen³

2015

IJCA

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In this paper, A new distribution called Exponential Lomax distribution is introduced. It is seemed that the parameter values of our new distribution are depending on decreasing and upside-down bathtub failure rate function. Also, the statistical properties of this model are studied, such as, quantiles, moments, mean deviation. Moreover, maximum likelihood estimators of it ' s parameters are discussed. Finally, the procedure is illustrated by real data set. It is shown that the introduced model is more competitive than other models.

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Traffic characteristics of aggregated module downloads for mobile terminal reconfiguration

Cited by 39 publications

References 6 publications

On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution

On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution

Assessing Transfer Functions in Control Systems

Exponential Lomax Distribution

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