A flexible nonlinear modelling framework for nonstationary generalized extreme value analysis in hydroclimatology

Hydrological Processes

Volumn 24, Issue 6, 2010, Pages 673-685

  Cannon, Alex J ^a  

^a ENVIRONMENT CANADA   (Canada)

Author keywords

Extreme value analysis; Neural network; Nonlinear hydroclimatology; Nonstationary; Statistical modelling

Indexed keywords

AKAIKE INFORMATION CRITERION; BAYESIAN INFORMATION CRITERION; CLIMATIC VARIABILITY; CONDITIONAL DENSITY; COVARIATES; EXTREME VALUE ANALYSIS; GENERALIZED EXTREME VALUE; GENERALIZED MAXIMUM LIKELIHOOD; HYDROCLIMATOLOGY; MODEL COMPLEXITY; MODEL PARAMETERS; MONTE CARLO SIMULATION; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; NON-LINEAR MODELLING; NON-STATIONARITIES; NONSTATIONARY; ON TIME; PRECIPITATION DATA; PROBABILISTIC EXTENSION; SMALL SAMPLE SIZE; SOUTHERN CALIFORNIA; STATISTICAL MODELLING; SYNTHETIC PROBLEM;

COMPUTER SIMULATION; MAXIMUM LIKELIHOOD ESTIMATION; MONTE CARLO METHODS; NONLINEAR ANALYSIS; PROBABILITY DISTRIBUTIONS; TIME SERIES; TIME SERIES ANALYSIS; VALUE ENGINEERING;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; BAYESIAN ANALYSIS; CLIMATE VARIATION; CLIMATOLOGY; COMPUTER SIMULATION; HYDROMETEOROLOGY; MODELING; MONTE CARLO ANALYSIS; PRECIPITATION ASSESSMENT; STATISTICAL ANALYSIS;

CALIFORNIA; UNITED STATES;

EID: 77949600582     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.7506     Document Type: Article

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