Modeling and forecasting river flows by means of filtered Poisson processes
type: Item
instance of: scholarly article
title: Modeling and forecasting river flows by means of filtered Poisson processes
zbMATH Open document ID: 1428.86003
author: Mario Lefebvre
author: Fatima Bensalma
published in: Applied Mathematical Modelling
publication date: 2018-12-18T00:00:00Z
Mathematics Subject Classification ID: 86A05
Mathematics Subject Classification ID: 60G55
Mathematics Subject Classification ID: 60K10
zbMATH DE Number: 6995100
zbMATH Keywords: response function
zbMATH Keywords: estimation
zbMATH Keywords: forecasting
zbMATH Keywords: conditional expectation
zbMATH Keywords: autoregressive model
MaRDI profile type: Publication
full work available at URL: j.apm.2014.05.027
OpenAlex ID: W2066691563
cites work: Using filtered Poisson processes to model a river flow
cites work: Q3293721
cites work: On the shot-noise streamflow model and its applications
cites work: Conceptually-based shot noise modeling of streamflows at short time interval
cites work: A filtered renewal process as a model for a river flow
cites work: A theoretical note on the distribution of a filtered compound doubly stochastic Poisson process
DOI: 10.1016/J.APM.2014.05.027
description: scientific article; zbMATH DE number 6995100