“…Thus, tin this work the statistical analyses of the model evaluations for obtaining confidence intervals for safety parameters estimates rely on the use of Order Statistics (OS), along a non-parametric approach initially explored by [Wilks, 1941;Wilks, 1942]; this brings the advantage that the number of code calculations needed for safety margins evaluation is independent of the number of uncertain input parameters and provides a given confidence on the reliability of the calculated point-estimate obtained with a limited number of code runs. Figure 1 shows a schematic sketch of the non-parametric procedure here adopted [Secchi et al, 2008]; for ease of illustration, a single safety parameter y is considered.…”
Section: Notation and List Of Acronymsmentioning
confidence: 99%
“…In this case, the confidence in the estimates becomes crucial for decision making and must, thus, be quantified [Wilks, 1941;Wilks, 1942;Guba et al, 2003;Nutt et al, 2004].…”
Section: Estimation Of Safety Marginsmentioning
confidence: 99%
“…These can be used to estimate a given percentile of the safety margin probability distribution. To obtain the desired confidence in the safety margin percentile, the number N of code runs is defined on the basis of the Order Statistics (OS) methodology, in its nonparametric formulation which applies independently from the type of probability distribution of the output data under study (in this case unknown) [Wilks, 1941;Wilks, 1942]. As we shall see, this amounts to ordering the elements of the random sample by increasing value, the element in the r th place being the statistic of order r, and using the order statistics for estimating the percentiles of the distribution (Section 2.4) with the desired confidence.…”
“…Thus, tin this work the statistical analyses of the model evaluations for obtaining confidence intervals for safety parameters estimates rely on the use of Order Statistics (OS), along a non-parametric approach initially explored by [Wilks, 1941;Wilks, 1942]; this brings the advantage that the number of code calculations needed for safety margins evaluation is independent of the number of uncertain input parameters and provides a given confidence on the reliability of the calculated point-estimate obtained with a limited number of code runs. Figure 1 shows a schematic sketch of the non-parametric procedure here adopted [Secchi et al, 2008]; for ease of illustration, a single safety parameter y is considered.…”
Section: Notation and List Of Acronymsmentioning
confidence: 99%
“…In this case, the confidence in the estimates becomes crucial for decision making and must, thus, be quantified [Wilks, 1941;Wilks, 1942;Guba et al, 2003;Nutt et al, 2004].…”
Section: Estimation Of Safety Marginsmentioning
confidence: 99%
“…These can be used to estimate a given percentile of the safety margin probability distribution. To obtain the desired confidence in the safety margin percentile, the number N of code runs is defined on the basis of the Order Statistics (OS) methodology, in its nonparametric formulation which applies independently from the type of probability distribution of the output data under study (in this case unknown) [Wilks, 1941;Wilks, 1942]. As we shall see, this amounts to ordering the elements of the random sample by increasing value, the element in the r th place being the statistic of order r, and using the order statistics for estimating the percentiles of the distribution (Section 2.4) with the desired confidence.…”
“…He obtained a nonparametric R-reliable interval, for x. Wilks [2] has given an extensive survey of order statistics and their applications to R-reliablp intervals and has given an extensive list of references on the subject.…”
Section: Abstract (Continue On Reverse If Necessary and Identify By Bmentioning
“…The number of samples N S necessary for obtaining these bounds is derived from the Wilks theory (CSNI, 2007;Wilks, 1941Wilks, , 1942. It uses the order statistics and says that when there is an N-sample of a random variable ordered (as the collection efficiency):…”
Section: Input Parameters Uncertainty Applied To Ari3sgmentioning
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