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Journal ArticleDOI

L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics

Jonathan R. M. Hosking
- 01 Sep 1990 - 
- Vol. 52, Iss: 1, pp 105-124
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TLDR
The authors define L-moments as the expectations of certain linear combinations of order statistics, which can be defined for any random variable whose mean exists and form the basis of a general theory which covers the summarization and description of theoretical probability distributions.
Abstract
L-moments are expectations of certain linear combinations of order statistics. They can be defined for any random variable whose mean exists and form the basis of a general theory which covers the summarization and description of theoretical probability distributions, the summarization and description of observed data samples, estimation of parameters and quantiles of probability distributions, and hypothesis tests for probability distributions. The theory involves such established procedures as the use of order statistics and Gini's mean difference statistic, and gives rise to some promising innovations such as the measures of skewness and kurtosis and new methods of parameter estimation

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Citations
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Journal ArticleDOI

A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index

TL;DR: In this article, a new climatic drought index, the standardized precipitation evapotranspiration index (SPEI), is proposed, which combines multiscalar character with the capacity to include the effects of temperature variability on drought assessment.
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A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006

TL;DR: In this paper, the authors presented a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950-2006.
Journal ArticleDOI

Statistics of extremes in hydrology

TL;DR: In this article, statistical downscaling of hydrologic extremes is considered, and future challenges such as the development of more rigorous statistical methodology for regional analysis of extremes, as well as the extension of Bayesian methods to more fully quantify uncertainty in extremal estimation are reviewed.
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Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring

TL;DR: In this paper, the authors present a collection of 25 figs from the genus "Figs" and discuss the relationship between the two types of figs: figs and figs.
References
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Book

Linear statistical inference and its applications

TL;DR: Algebra of Vectors and Matrices, Probability Theory, Tools and Techniques, and Continuous Probability Models.
Journal ArticleDOI

Linear Statistical Inference and its Applications

TL;DR: The theory of least squares and analysis of variance has been studied in the literature for a long time, see as mentioned in this paper for a review of some of the most relevant works. But the main focus of this paper is on the analysis of variance.
Book

Approximation Theorems of Mathematical Statistics

TL;DR: In this paper, the basic sample statistics are used for Parametric Inference, and the Asymptotic Theory in Parametric Induction (ATIP) is used to estimate the relative efficiency of given statistics.
Book ChapterDOI

A Class of Statistics with Asymptotically Normal Distribution

TL;DR: In this article, the authors considered the problem of estimating a U-statistic of the population characteristic of a regular functional function, where the sum ∑″ is extended over all permutations (α 1, α m ) of different integers, 1 α≤ (αi≤ n, n).
Journal ArticleDOI

The Laplace Transform

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