Objective data evaluation procedures

Gray, P.W.; Mahon, T.D. Mac; Rajput, Muhammad Usman

doi:10.1016/0168-9002(90)90918-v

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…These quantities behave very much like the usual average and its standard deviation. The bootstrap method presented here is the method with the simplest set of requirements from all usual methods of dealing with discrepant data set, since it requires only the unbiasedness of the data; the other methods [1][2][3][4][5] require the unbiasedness and other hypothesis. Moreover, the existence of one strongly biased datum (or a few data in a large data set) does not affect the BM estimate as was shown in section II.3., in contrast to many other methods.…”

Section: Discussionmentioning

confidence: 99%

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Characteristics of the Bootstrap Estimate of Discrepant Data Sets

Helene¹,

Vanin²,

Castro³

2002

Journal of Nuclear Science and Technology

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We present in this paper a Bootstrap Method to estimate a best value and its standard deviation for a discrepant set of data. The method is applied to the determination of the half-lives of 137 Cs, 90Sr, 252Cf, Tritium, 35 S, 55Fe, and 99Mo. The self-consistency of the method and its capability to reject outliers was tested with good results. The application of the method to the determination of covariance matrices was tried, with poor results.

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Section: Discussionmentioning

confidence: 99%

“…[1][2][3][4][5] All the proposed procedures, however, assume that incorrect uncertainties are responsible for the data discrepancy, and modify them usually by a common factor, keeping unchanged the central values.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of the Bootstrap Estimate of Discrepant Data Sets

Helene¹,

Vanin²,

Castro³

2002

Journal of Nuclear Science and Technology

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“…Another procedure to compute the WM uncertainty was proposed by Gray et al (1990). It uses Bayesian approach and is recommended by the authors for evaluation of experimental data in case of doubt about correctness of reported uncertainties.…”

Section: Statistical Methods Usedmentioning

confidence: 99%

“…Many authors, e.g., Reid (1993); Surdin (1999); Nikiforov (2004) and Foster & Cooper (2010) discussed the long-term trends in R 0 estimates. Reid (1993); Surdin (1999) and Nikiforov (2004) showed the large negative slope in the 1970s to the beginning of the 1990s, As to the last 20 years, Surdin (1999) showed practically no drift for 1990-1998, Nikiforov (2004 showed zero or maybe small positive drift for 1990-2003, and Foster & Cooper (2010 revealed the large positive slope for 1992-2010.…”

Section: Input R 0 Determinationsmentioning

confidence: 96%

The current best estimate of the Galactocentric distance of the Sun based on comparison of different statistical techniques

Malkin¹

2012

Preprint

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In this paper, the current best estimate of a fundamental Galactic parameter Galactocentric distance of the Sun R 0 has been evaluated using all the available estimates published during the last 20 years. Unlike some other studies, our analysis of these results showed no statistically significant trend in R 0 during this period. However we revealed a statistically valuable improvement in the R 0 uncertainties with time of about 0.2 kpc for 20 years. Several statistical techniques have been used and compared to obtain the most reliable common mean of 52 determinations made in 1992-2011 and its realistic uncertainty. The statistical methods used include unweighted mean, seven variants of the weighted mean, and two variants of median technique. The R 0 estimates obtained with these methods range from 7.91 to 8.06 kpc with uncertainties varying from 0.05 to 0.08 kpc. The final value derived in this analysis is R 0 = 7.98±0.15 | stat ±0.20 | syst kpc, which can be recommended as the current best estimate of the Galactocentric distance of the Sun. For most of the practical applications the value of R 0 = 8.0 ± 0.25 kpc can be used.

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“…Alternative Bayesian (BAYS) [10] and modified Bayesian (MBAYS) [11] procedures assume that nothing is known about the extent to which the experimenters incorrectly estimated their uncertainties, and considering the prior probability density function of experimental uncertainties, propose to use the final standard uncertainty, increased by [χ 2 / (n − 3)] 1/2 for BAYS or [χ 2 / (n − 2)] 1/2 for MBAYS (where n is the number of input values), respectively. Examples of utilization of these procedures are given in the publication [12].…”

Section: Statistical Processmentioning

confidence: 99%

Uncertainties in nuclear decay data evaluations

Bé¹,

Chechev²,

Pearce³

2015

Metrologia

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Over the years, scientists have compiled and evaluated experimental results and combined these with theoretical studies with the goal of obtaining the best values, and their uncertainties, for the quantities related to radioactive decay. To meet the demand, an international group, the Decay Data Evaluation Project, was organised in 1995. The methodology adopted by this group is detailed. Some examples are given explaining how the final uncertainties are assessed from the experimental results and their uncertainties.

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Objective data evaluation procedures

Cited by 11 publications

References 5 publications

Characteristics of the Bootstrap Estimate of Discrepant Data Sets

Characteristics of the Bootstrap Estimate of Discrepant Data Sets

The current best estimate of the Galactocentric distance of the Sun based on comparison of different statistical techniques

Uncertainties in nuclear decay data evaluations

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