Bayesian inference from type II doubly censored Rayleigh data

Fernández, Arturo J.

doi:10.1016/s0167-7152(00)00021-3

Cited by 72 publications

(24 citation statements)

References 6 publications

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“…Our goal is to approximate how many comments a given post will receive using only the first few minutes/hours of the activity it generates as evidence. This is related to the problem of predictive inference of future responses, for which in the case of LN models several analytical studies [9,11] found estimators of the single future response density (i.e. the probability of the next comment) using a subset of the data.…”

Section: Introductionmentioning

confidence: 99%

Description and Prediction of Slashdot Activity

Kaltenbrunner¹,

Gómez²,

López³

2007

2007 Latin American Web Conference (LA-WEB 2007)

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Section: Introductionmentioning

confidence: 99%

Description and Prediction of Slashdot Activity

Kaltenbrunner¹,

Gómez²,

López³

2007

2007 Latin American Web Conference (LA-WEB 2007)

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“…Howlader (1985) presented HPD-prediction intervals for the z th order statistic of a future sample. Fernández (2000) considered the problem of predicting an independent future sample from the Rayleigh distribution under doubly Type II censoring scheme. Raqab and Madi (2002) considered an estimation of the predictive distribution of the total time on a test up to certain failures in a future sample, as well as that of the remaining testing time until all the units in the original sample have failed.…”

Section: Prediction Of Remaining Lifetimes Truncated At X(m)mentioning

confidence: 99%

Hierarchical Bayes Estimation of Reliability Indexes of Cold Standby Series System under General Progressive Type II Censoring Scheme

Barot¹,

Patel²

2016

J. Mod. App. Stat. Meth.

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“…However we attempt to fit the data with even better accuracy. Models following Rayleigh distribution (Fernández, 2000) or Weibull functions (Weibull, 1951) do not fit the data properly. Thus we propose the model of the following type…”

Section: Spectramentioning

confidence: 99%

Lexical Computational Models: The Case of the Byzantine Greek Language

Myridis¹

2010

RES

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In this article in-depth analysis and processing of dictionaries' corpora is presented, based on e-collections of them. Moreover special interest is given to the development of means and tools for the coupling of lexica to (speech or textual) linguistic corpora. The relative results are (a) the construction of solutions for language processing based on lexicons' prior information and infrastructure, as well as (b) the development of adequate models for fitting and representation of real, lexical or language, data. Applications of language processing relative to (a) metric measurements (b) distributions and (c) spectra are given. Analytical models, developed in order to fit real measurements in lexica, are constructed, with expansion to language processing. As an instance, the e-corpus of the Medieval Greek Language regarding the period 1100AD-1669AD [expanding from Middle Byzantine era to Late Byzantine period and then to Post-Byzantine years], based on the renowned dictionary of Prof.Kriaras, has been constructed. Elements and results of the aforementioned language processing are given. This kind of processing is performed for the first time regarding the Greek language.

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Bayesian inference from type II doubly censored Rayleigh data

Cited by 72 publications

References 6 publications

Description and Prediction of Slashdot Activity

Description and Prediction of Slashdot Activity

Hierarchical Bayes Estimation of Reliability Indexes of Cold Standby Series System under General Progressive Type II Censoring Scheme

Lexical Computational Models: The Case of the Byzantine Greek Language

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