Parameter Estimation for the Truncated Pareto Distribution

By I. Aban, Mark M. Meerschaert, Anna K. Panorska. 2006

323 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/edd77e37216ad41d464af08900ba28e073cf16fe

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Citations in the corpus

Productive Cities: Sorting, Selection, and Agglomeration (2014, unknown): “….0030 .0035 .9764 1.0802 1/256 .0007 .0010 1.0216 1.0392 1/512 .0002 .0003 .9926 1.0328 * ML estimates for the truncated Pareto distribution follow Aban et al. ð2006Þ and are computed from random samples of 1,000 observations that are generated using inverse transform sampling. y OLS…”
Aquifer operator scaling and the effect on solute mixing and dispersion (2006, background): “The distribution of K or ln(K) is typically heavier tailed than a Gaussian [Eggleston et al., 1996; Painter and Paterson, 1994; Painter, 1996, 2001; Rasmussen et al., 1993; Liu and Molz, 1996, 1997; Benson et al., 2001; Hyun and Neuman, 2003; Meerschaert et al., 2004; Aban et al., 2006].”
Fitting and goodness-of-fit test of non-truncated and truncated power-law distributions (2012, methodology): “In such situations a simple generalization is the truncation of the tail (Aban et al., 2006; Burroughs and Tebbens, 2001; Johnson et al., 1994), yielding the truncated power-law distribution, defined in the same way as before by f (x) ∝ 1/xα but with a ≤ x ≤ b, with b finite, and with normalizing…”
Bibliography on stable distributions, processes and related topics (2004, background): “Nolan and Rajput (1995), Abdul-Hamid (1996), Abdul-Hamid and Nolan (1998), Nolan (2015b), Nolan (2005), Matsui and Takemura (2008b), Nolan (2013).”
Variation in above-ground forest biomass across broad climatic gradients (2011, background): “So that f(M) is a valid probability density function, in the form of the truncated Pareto (Page, 1968; Aban et al., 2006), the coefficient, c, is defined as α α α + ( ) − ( ) + + − 1 1 1 1 M M max min (see White et al.”
Time and space nonlocalities underlying fractional-derivative models: Distinction and literature review of field applications (2009, background): “Pareto distributions of hydraulic conductivity (with a heavy tail for large values) observed in the field (see for example, [1]) supports the assumption of positively skewed particle displacements.”
On the Levy-Walk Nature of Human Mobility (2008, methodology): “We apply Maximum Likelihood Estimation (MLE) to fit three known distributions, exponential, log-normal, and truncated Pareto distributions [12] to the CCDF.”
The beta-Pareto distribution (2008, background): “[8] contains a detailed list of important areas where heavy-tailed distributions are found applicable.”