scholarly journals Estimating extreme dry-spell risk in the middle Ebro valley (northeastern Spain): a comparative analysis of partial duration series with a general Pareto distribution and annual maxima series with a Gumbel distribution

2003 ◽  
Vol 23 (9) ◽  
pp. 1103-1118 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
S. Beguería-Portugués
Keyword(s):  
Comparative Analysis ◽  
Pareto Distribution ◽  
Gumbel Distribution ◽  
Partial Duration Series ◽  
Ebro Valley ◽  
Dry Spell ◽  
General Pareto Distribution

scholarly journals Estimating extreme dry spell risk in Ichkeul Lake Basin (Northern Tunisia): a comparative analysis of annual maxima series with a Gumbel distribution

2020 ◽  
Vol 383 ◽  
pp. 241-248
Author(s):  
Majid Mathlouthi ◽  
Fethi Lebdi
Keyword(s):  
Daily Precipitation ◽  
Gumbel Distribution ◽  
Lake Basin ◽  
Climatic Variable ◽  
Rainfall Events ◽  
Northern Tunisia ◽  
Dry Spell ◽  
Ichkeul Lake ◽  
Threshold Amount ◽  
Annual Maximum Series

Abstract. This paper analyses a 42 year time series of daily precipitation in Ichkeul Lake Basin (northern Tunisia) in order to predict extreme dry-spell risk. Dry events are considered as a sequence of dry days separated by rainfall events from each other. Thus the rainy season is defined as a series of rainfall and subsequent dry events. Rainfall events are defined as the uninterrupted sequence of rainy days, when at last on one day more than a threshold amount of rainfall has been observed. A comparison of observed and estimated maximum dry events (42 year return period) showed that Gumbel distribution fitted to annual maximum series gives better results than the exponential (E) distribution combined with partial duration series (PDS). Indeed, the classical Gumbel approach slightly underestimated the empirical duration of dry events. The AMS–G approach was successfully applied in the study of extreme hydro-climatic variable values. The results reported here could be applied in estimating climatic drought risks in other geographical areas.

Modeling biometric systems using the general pareto distribution (GPD)

2008 ◽  
Author(s):  
Zhixin Shi ◽  
Frederick Kiefer ◽  
John Schneider ◽  
Venu Govindaraju
Keyword(s):  
Pareto Distribution ◽  
Biometric Systems ◽  
General Pareto Distribution

scholarly journals A Monte Carlo simulation of multivariate general Pareto distribution and its application

2014 ◽  
Vol 11 (6) ◽  
pp. 2733-2753 ◽  
Author(s):  
L. Yao ◽  
W. Dongxiao ◽  
Z. Zhenwei ◽  
H. Weihong ◽  
S. Hui
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Pareto Distribution ◽  
Joint Probability ◽  
Simulation Method ◽  
Value Theory ◽  
Extreme Value ◽  
Marine Environmental ◽  
General Pareto Distribution ◽  
Hydrological Station

Abstract. This paper presents a multivariate general Pareto distribution (MGPD) method and builds a method for solving MGPD through the use of a Monte Carlo simulation for marine environmental extreme-value parameters. The simulation method has proven to be feasible in the analysis of the joint probability of wave height and its concomitant wind from a hydrological station in the South China Sea (SCS). The MGPD is the natural distribution of the multivariate peaks-over-threshold (MPOT) sampling method, and is based on the extreme-value theory. The existing dependence functions can be used in the MGPD, so it may describe more variables which have different dependence relationships. The MGPD method improves the efficiency of the extremes in raw data. For the wave and the concomitant wind from a period of 23 years (1960–1982), the number of the wave and wind selected is averaged to 19 per year. For the joint conditional probability of the MGPD, the relative error is rather small in the Monte Carlo simulation method.

Analysis of power law assumptions for short-period comets and Kuiper bodies

1999 ◽  
Vol 173 ◽  
pp. 289-293 ◽  
Author(s):  
J.R. Donnison ◽  
L.I. Pettit
Keyword(s):  
Power Law ◽  
Pareto Distribution ◽  
Limited Data ◽  
Short Period ◽  
Probability Plots ◽  
Exponential Probability

AbstractA Pareto distribution was used to model the magnitude data for short-period comets up to 1988. It was found using exponential probability plots that the brightness did not vary with period and that the cut-off point previously adopted can be supported statistically. Examination of the diameters of Trans-Neptunian bodies showed that a power law does not adequately fit the limited data available.

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