A statistical rainfall-runoff mixture model with heavy-tailed components

Water Resources Research

Volumn 45, Issue 10, 2009, Pages

  Carreau, J ^a   Naveau, P ^a   Sauquet, E ^b  

^a CNRS   (France)

^b CENTRE DE LYON VILLEURBANNE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CONDITIONAL DENSITY; CONFIDENCE INTERVAL; COVARIATES; EXTREME QUANTILES; EXTREME VALUE THEORY; GAUSSIANS; GENERALIZED PARETO DISTRIBUTIONS; HEAVY-TAILED; LEVEL 5; LOG LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATOR; MIXTURE MODEL; NON-PARAMETRIC; PENALTY TERM; RAINFALL RUNOFF; RIVER RUNOFFS; SMALL TRAINING; SYNTHETIC DATA; TAIL INDEX;

MAXIMUM LIKELIHOOD; MIXTURES; NEURAL NETWORKS; PROBABILITY DENSITY FUNCTION; WIND EFFECTS;

RUNOFF;

ARTIFICIAL NEURAL NETWORK; CONFIDENCE INTERVAL; GAUSSIAN METHOD; MAXIMUM LIKELIHOOD ANALYSIS; NUMERICAL MODEL; RAINFALL-RUNOFF MODELING;

FRANCE; ILE DE FRANCE; ORGEVAL BASIN; YVELINES;

EID: 72149129445     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2009WR007880     Document Type: Article

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