Handling of Model Error: The Deterministic–Stochastic Model and Its Prediction Updating

2017 ◽  
pp. 131-144
Keyword(s):  
Stochastic Model ◽  
Model Error

scholarly journals The Role of Stochastic Model Error Perturbations in Predicting the 2011/12 Double-Dip La Niña

SOLA ◽  
2015 ◽  
Vol 11 (0) ◽  
pp. 65-69 ◽  
Author(s):  
Lisha Feng ◽  
Fei Zheng ◽  
Jiang Zhu ◽  
Haiwen Liu
Keyword(s):  
Stochastic Model ◽  
Model Error ◽  
La Niña ◽  
La Nina

A Fruitful Stochastic Model

1964 ◽  
Vol 9 (7) ◽  
pp. 273-276
Author(s):  
ANATOL RAPOPORT
Keyword(s):  
Stochastic Model

A Stochastic Model for Evolution of Altruistic Genes

1996 ◽  
Vol 6 (4) ◽  
pp. 445-453 ◽  
Author(s):  
Roberta Donato
Keyword(s):  
Stochastic Model

Reduced model error analysis “application to synchronous machines"

1994 ◽  
Vol 4 (10) ◽  
pp. 1999-2012 ◽  
Author(s):  
Nabil Derbel ◽  
Mohamed B.A. Kamoun ◽  
Michel Poloujadoff
Keyword(s):  
Error Analysis ◽  
Model Error ◽  
Synchronous Machines ◽  
Reduced Model ◽  
Analysis Application

A Stochastic Model for the Inheritance of the Cancer Proneness Phenotype

1987 ◽  
Vol 26 (03) ◽  
pp. 117-123
Author(s):  
P. Tautu ◽  
G. Wagner
Keyword(s):  
Stochastic Model ◽  
Gaussian Process ◽  
Covariance Function ◽  
Neoplastic Disease ◽  
Disease Phenotype ◽  
Probabilistic Representation ◽  
Temporal Behaviour ◽  
Continuous Trait ◽  
Continuous Parameter ◽  
Level Zero

SummaryA continuous parameter, stationary Gaussian process is introduced as a first approach to the probabilistic representation of the phenotype inheritance process. With some specific assumptions about the components of the covariance function, it may describe the temporal behaviour of the “cancer-proneness phenotype” (CPF) as a quantitative continuous trait. Upcrossing a fixed level (“threshold”) u and reaching level zero are the extremes of the Gaussian process considered; it is assumed that they might be interpreted as the transformation of CPF into a “neoplastic disease phenotype” or as the non-proneness to cancer, respectively.

Stochastic Model of Traffic Jam and Traffic Signal Control

2011 ◽  
Vol 131 (2) ◽  
pp. 303-310
Author(s):  
Ji-Sun Shin ◽  
Cheng-You Cui ◽  
Tae-Hong Lee ◽  
Hee-hyol Lee
Keyword(s):  
Stochastic Model ◽  
Traffic Signal ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Traffic Jam
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