Accounting for structural error and uncertainty in a model: An approach based on model parameters as stochastic processes

Environmental Modelling and Software

Volumn 27-28, Issue , 2012, Pages 97-111

  Lin, Zhulu ^a   Beck, M Bruce ^b  

^a North Dakota State University   (United States)

^b UNIVERSITY OF GEORGIA   (United States)

Author keywords

Climate change; Conceptual error; Model averaging; Model structure error and uncertainty; Recursive estimation; Stochastic processes

Indexed keywords

BAYESIAN MODEL AVERAGING; FILTERING THEORY; FORECASTING ERROR; GAIN MATRICES; GENERALIZED RANDOM WALKS; INPUT DISTURBANCE; MODEL AVERAGING; MODEL FITTING; MODEL PARAMETERS; PARAMETRIC UNCERTAINTIES; PREDICTIVE TEST; RECURSIVE ESTIMATION; STOCHASTIC PROCESS; STRUCTURAL ERRORS;

BAYESIAN NETWORKS; BIOLOGICAL SYSTEMS; CLIMATE CHANGE; ERRORS; FORECASTING; RANDOM PROCESSES; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; SYSTEMATIC ERRORS;

CLIMATE MODELS;

ALGORITHM; BAYESIAN ANALYSIS; CALIBRATION; CLIMATE CHANGE; ENVIRONMENTAL EFFECT; ENVIRONMENTAL POLICY; ENVIRONMENTAL PROTECTION; ERROR ANALYSIS; FILTER; FORECASTING METHOD; IDENTIFICATION METHOD; NUMERICAL MODEL; REMEDIATION; STOCHASTICITY; UNCERTAINTY ANALYSIS;

EID: 84855547766     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2011.08.015     Document Type: Article

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