2015
DOI: 10.1103/physreve.91.052124
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Fractional Edgeworth expansion: Corrections to the Gaussian-Lévy central-limit theorem

Abstract: In this article we generalize the classical Edgeworth expansion for the probability density function (PDF) of sums of a finite number of symmetric independent identically distributed random variables with a finite variance to PDFs with a diverging variance, which converge to a Lévy α-stable density function. Our correction may be written by means of a series of fractional derivatives of the Lévy and the conjugate Lévy PDFs. This series expansion is general and applies also to the Gaussian regime. To describe t… Show more

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Cited by 9 publications
(7 citation statements)
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“…Data analyses were performed on SPSS for Mac OS X, Version 22.0 (SPSS Inc., Chicago IL) with a 95% confidence interval (CI) and considering statistically significant differences if P value < 0.05. Parametric tests were used because the sample size (greater than 30 subjects per group) was sufficient to be supported by the central limit theorem [ 29 ]. The continuous variables are presented as mean and standard deviation (SD), and the categorical variables are presented as absolute numbers and relative frequency (i.e., percentages).…”
Section: Methodsmentioning
confidence: 99%
“…Data analyses were performed on SPSS for Mac OS X, Version 22.0 (SPSS Inc., Chicago IL) with a 95% confidence interval (CI) and considering statistically significant differences if P value < 0.05. Parametric tests were used because the sample size (greater than 30 subjects per group) was sufficient to be supported by the central limit theorem [ 29 ]. The continuous variables are presented as mean and standard deviation (SD), and the categorical variables are presented as absolute numbers and relative frequency (i.e., percentages).…”
Section: Methodsmentioning
confidence: 99%
“…In contrast the Gaussian cannot be matched to the ID for intermediate values of x. To make the matching, one needs to find the correction to the central limit theorem, for example using the fractional Edgeworth expansion [26]. This could yield a power law correction term to the Gaussian which could in principle match the ID.…”
Section: +1mentioning
confidence: 99%
“…Descriptive statistics were generated for the sociodemographic data (such as age, BMI, chronicity time, pain intensity, and others). Manuscript to be reviewed showed that the majority of the variables were normally distributed in the sample, so parametric tests were used because of the central limit theorem for samples >50 subjects per group (Mouri, 2013;Hazut et al, 2015). Continuous variables are presented as mean and standard deviation, and the categorical variables are presented as absolute numbers and relative frequency (percentages).…”
Section: Discussionmentioning
confidence: 99%