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Probability function estimation for the maximum precipitation model using kernel estimators

Object's details: Probability function estimation for the maximum precipitation model using kernel estimators

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Provider:Biblioteka Cyfrowa Politechniki Koszalińskiej

Description

Title:
Probability function estimation for the maximum precipitation model using kernel estimators
Creator:
Karczewski, Maciej;
Kaźmierczak, Bartosz;
Michalski, Andrzej;
Kuchar, Leszek
Description:
The distribution of maximum rainfall level is not a homogeneous phenomenon and is often characterized by multimodality, and often the phenomenon of heavy right-hand tail. Modelling this phenomenon using classic probability distributions leads to ignoring multimodality, and thus underestimating or overestimating the predicted values in the tail tails – the most important from the point of view of safe dimensioning of drainage systems. To avoid the abovementioned difficulties, a non-parametric kernel estimator method of maximum precipitation density function was used (on the example of rainfall data from a selected station in Poland). The methodology proposed in the paper (for use on any rainfall data from other meteorological stations) will allow the development of more reliable local models of maximum precipitation.
Object availability:
free access
Rights: Creative Commons BY-SA 4.0
Date:
2022.12.31;
2022
Type:
artykuł w czasopiśmie
Language:
English
Publisher:
Politechnika Koszalińska
Subject:
maximum precipitation;
kernel estimation
Data provider:
Biblioteka Cyfrowa Politechniki Koszalińskiej

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FBC TeNe Project

Project co-financed by European Funds under the Operational Program Digital Poland for 2014-2020 (project no. POPC.02.04.00-00-0012 / 20-00)

More information about the project can be found at: https://tene.fbc.pionier.net.pl

European Funds. Digital Poland

Republic of Poland

Digital Libraries Federation

European Union - European Regional Development Fund

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