scholarly journals SIMULATION OF SEA STORMS INCLUDING MULTIVARIATE STORM EVOLUTION

2018 ◽  
pp. 35
Author(s):  
Sebastián Solari ◽  
Miguel A. Losada
Keyword(s):  
Probability Distribution ◽  
Autoregressive Model ◽  
Joint Probability ◽  
New Method ◽  
Joint Probability Distribution ◽  
Northern Coast ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive ◽  
Storm Evolution

A new method for the simulation of storms is proposed which takes into account the multivariate evolution of the storms, allowing to innovate in the form of each simulated storm, for all the variables involved. The method is based on two novel aspects: (a) measured storms are grouped using clusters techniques and a set of average evolution forms is defined for each cluster, one for each of the variables involved, and (b) a Vector Autoregressive model is fitted to the differences between the average evolution of each variable and the actual measured evolutions. The ability of the methodology to properly reproduce the joint probability distribution of all the variables involved is demonstrated for a case study at the mid Rio de la Plata northern coast.

Regional Multiseverity Casualty Estimation Due to Building Damage following a Mw 8.8 Earthquake Scenario in Lima, Peru

2018 ◽  
Vol 34 (4) ◽  
pp. 1739-1761 ◽  
Author(s):  
Luis Ceferino ◽  
Anne Kiremidjian ◽  
Gregory Deierlein
Keyword(s):  
Probability Distribution ◽  
Joint Probability ◽  
Building Damage ◽  
Patient Treatment ◽  
Joint Probability Distribution ◽  
Model Parameters ◽  
Probabilistic Framework ◽  
Earthquake Scenario ◽  
Selection Of

This paper presents the application of a rigorous probabilistic framework that estimates the number, severity, and distribution of casualties over a region. A brief summary of the model is included in this paper. The application is for casualties resulting from a Mw 8.8 earthquake scenario occurring on the sub-duction fault along the coastline of Lima, Peru. The case study demonstrates an application of the casualty model, including the procedures for acquiring the required information, the selection of model parameters, and a step-by-step explanation of the model-solving algorithms. The model provides an estimate of the joint probability distribution of multiseverity casualties, including spatial and across-severity correlations. This paper also shows how the model can be useful for (1) estimating 90th-percentile casualties, (2) identifying unsafe communities and structural typologies, and (3) providing evidence to support hospital collaboration policies across different districts to increase the patient treatment reliability. Additionally, the results demonstrate that empirical fatality prediction methodologies can underestimate fatality rates in countries with scarce and outdated fatality data.

scholarly journals A Spatial Panel Structural Vector Autoregressive Model with Interactive Effects and Its Simulation

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 883
Author(s):  
Yaqing Liu ◽  
Hongbing Ouyang ◽  
Xiaolu Wei
Keyword(s):  
Autoregressive Model ◽  
Common Factors ◽  
Interactive Effects ◽  
Vector Autoregressive Model ◽  
Finite Sample ◽  
Vector Autoregressive ◽  
Spatial Panel ◽  
The Common ◽  
Structural Vector Autoregressive Model ◽  
Structural Vector

The existing spatial panel structural vector auto-regressive model can effectively capture the time and spatial dynamic dependence of endogenous variables. However, the hypothesis that the common factors have the same effect for all spatial units is unreasonable. Therefore, incorporating time effects, spatial effects, and time-individual effects, this paper develops a more general spatial panel structural vector autoregressive model with interactive effects (ISpSVAR) that can reflect the different effects of common factors on different spatial units. Additionally, based on whether or not the common factors can be observed, this paper proposes procedures to estimate ISpSVAR separately and studies the finite sample properties of estimators by Monte Carlo simulation. The simulation results show the effectiveness of the proposed ISpSVAR model and its estimation procedures.

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