scholarly journals Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential

2019 ◽  
Vol 124 (12) ◽  
pp. 9209-9234 ◽  
Author(s):  
D. Anderson ◽  
A. Rueda ◽  
L. Cagigal ◽  
J. A. A. Antolinez ◽  
F. J. Mendez ◽  
...  
Keyword(s):  
Flood Hazard ◽  
Time Varying ◽  
Hazard Potential ◽  
Coastal Flood ◽  
Short And Long Term ◽  
Term Analysis ◽  
Flood Hazard Potential

scholarly journals A Short-and Long-Term Analysis of the Nexus between Bitcoin, Social Media and Covid-19 Outbreak

Heliyon ◽  
2021 ◽  
pp. e07539
Author(s):  
Azza Bejaoui ◽  
Nidhal Mgadmi ◽  
Wajdi Moussa ◽  
Tarek Sadraoui
Keyword(s):  
Social Media ◽  
Short And Long Term ◽  
Term Analysis

scholarly journals A Portable Chemotaxis Platform for Short and Long Term Analysis

PLoS ONE ◽  
2012 ◽  
Vol 7 (9) ◽  
pp. e44995 ◽  
Author(s):  
Chenjie Xu ◽  
Yuk Kee C. Poh ◽  
Isaac Roes ◽  
Eoin D. O'Cearbhaill ◽  
Mads Emil Matthiesen ◽  
...  
Keyword(s):  
Short And Long Term ◽  
Term Analysis

Long Term Analysis of TLP Extreme Tendon Tensions Using a Coupled Model and Comparison With the Contour Line Approach

2017 ◽  
Author(s):  
Isabel Jimenez Puente ◽  
Gunnar Lian
Keyword(s):  
Coupled Model ◽  
Element Model ◽  
Contour Line ◽  
Probability Of Exceedance ◽  
Tension Response ◽  
Annual Probability ◽  
Short And Long Term ◽  
The Time Domain ◽  
Term Analysis

This paper presents a full long term analysis of a TLP extreme tendon tensions using the all seas approach, and its comparison to the results estimated by the contour line approach. The analysis of the TLP tendon tension response is performed in the time domain using a coupled model where the floater is modelled in the software SIMO, while the tendon system is represented by a Finite Element Model in RIFLEX, including therefore the effects of non-linear restoring from the tendon system and bending and deformations of the tendons. The characteristic tendon tensions with q-annual probability of exceedance are estimated from a full long term analysis where both the short and long term variability are considered. These results are then compared to those obtained through the long term estimate from the contour line approach when assuming the 90th percentile for the worst sea state with q-annual probability of exceedance. The results from the full long term analysis will allow us to verify the adequate percentile level to be used with a contour line approach when estimating extreme TLP tendon tensions.

Assessment of climate change impacts on flood hazard potential in the Alpine Lech watershed

2012 ◽  
Vol 460-461 ◽  
pp. 29-39 ◽  
Author(s):  
Christian Dobler ◽  
Gerd Bürger ◽  
Johann Stötter
Keyword(s):  
Climate Change ◽  
Flood Hazard ◽  
Climate Change Impacts ◽  
Hazard Potential ◽  
Flood Hazard Potential

scholarly journals INTRODUCTION TO TIME-VARYING MODELING WITH MACROECONOMIC AND FINANCIAL DATA

2012 ◽  
Vol 16 (S2) ◽  
pp. 167-175 ◽  
Author(s):  
Fredj Jawadi
Keyword(s):  
Time Series ◽  
Time Variation ◽  
Moving Average ◽  
Statistical Properties ◽  
Financial Data ◽  
Time Varying ◽  
Arch Model ◽  
Financial Variables ◽  
Short And Long Term

The dynamics of macroeconomic and financial series has evolved swiftly and asymmetrically since the end of the 1970s, and their statistical properties have also changed over time, suggesting complex relationships between economic and financial variables. The transformations can be explained by considerable changes in householder's behavior, market structures, and economic systems and by the alternation of exogenous shocks and financial crises that have affected the economic cycle, with significant evidence of time variation in the major economic variables. Hence, there is a need for new econometric protocols to take such changes into consideration. The introduction of ARMA (autoregressive moving average models) by Box and Jenkins (1970) led to the development of time-series econometrics, which had a major impact on the conceptual analysis of economic and financial data. This type of modeling offered a transition from a static setup to a new modeling process that reproduces the time-varying features of macroeconomic and financial series. However, the ARMA modeling system retains the constancy of the first and second moments, limits the phases of a cycle to symmetrical instances, and only reproduces the dynamics of stationary variables. It thus fails to adequately reproduce the nonstationary relationships between major economic and financial variables. Abrupt changes in economies and financial systems have given evidence of nonstationary series whose statistical properties are also time-varying, making it necessary to develop new econometric tools to capture the time variation of economic and financial series in the mean and in the variance, and to apprehend their dynamics in the short and long term. Among the most important and influential studies in the 1980s' econometrics literature were therefore those that dealt with the introduction of the ARCH (autoregressive conditional heteroskedasticity) model by Engle (1982) and the cointegration theory by Engle and Granger (1987). The ARCH model, which focuses on the time-varying features of volatility structure, was a major breakthrough, as it highlighted the importance of the second moment of time series, while the cointegration framework enabled the short- and long-term dynamics of nonstationary variables to be modeled.

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