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Artículos de revistas sobre el tema "Bivariate Failure Return Period"

Autor: Grafiati

Publicado: 10 de marzo de 2023

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1

Kang, Ling, Shangwen Jiang, Xiaoyong Hu, and Changwen Li. "Evaluation of Return Period and Risk in Bivariate Non-Stationary Flood Frequency Analysis." Water 11, no. 1 (2019): 79. http://dx.doi.org/10.3390/w11010079.

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The concept of a traditional return period has long been questioned in non-stationary studies, and the risk of failure was recommended to evaluate the design events in flood modeling. However, few studies have been done in terms of multivariate cases. To investigate the impact of non-stationarity on the streamflow series, the Yichang station in the Yangtze River was taken as a case study. A time varying copula model was constructed for bivariate modeling of flood peak and 7-day flood volume, and the non-stationary return period and risk of failure were applied to compare the results between st

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2

Latif, Shahid, and Firuza Mustafa. "Bivariate Hydrologic Risk Assessment of Flood Episodes using the Notation of Failure Probability." Civil Engineering Journal 6, no. 10 (2020): 2002–23. http://dx.doi.org/10.28991/cej-2020-03091599.

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Floods are becoming the most severe and challenging hydrologic issue at the Kelantan River basin in Malaysia. Flood episodes are usually thoroughly characterized by flood peak discharge flow, volume and duration series. This study incorporated the copula-based methodology in deriving the joint distribution analysis of the annual flood characteristics and the failure probability for assessing the bivariate hydrologic risk. Both the Archimedean and Gaussian copula family were introduced and tested as possible candidate functions. The copula dependence parameters are estimated using the method-of

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3

Tosunoğlu, Fatih, Gianfausto Salvadori, and Muhammet Yilmaz. "Multivariate Assessment of Low-Flow Hazards via Copulas: The Case Study of the Çoruh Basin (Turkey)." Water 12, no. 10 (2020): 2848. http://dx.doi.org/10.3390/w12102848.

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Bivariate modeling and hazard assessment of low flows are performed exploiting copulas. 7-day low flows observed, respectively, in the upper, middle and lower parts of the Çoruh basin (Turkey) are examined, considering three pairs of certified stations located in different sub-basins. A thorough statistical analysis indicates that the GEV distribution can be used to model the marginal behavior of the low-flow. The joint distributions at each part are modeled via a dozen of copula families. As a result, the Husler–Reiss copula adequately fits the joint low flows in the upper part, while the t-S

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4

Gu, Lei, Jie Chen, Jiabo Yin, et al. "Projected increases in magnitude and socioeconomic exposure of global droughts in 1.5 and 2 °C warmer climates." Hydrology and Earth System Sciences 24, no. 1 (2020): 451–72. http://dx.doi.org/10.5194/hess-24-451-2020.

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Abstract. The Paris Agreement sets a long-term temperature goal to hold global warming to well below 2.0 ∘C and strives to limit it to 1.5 ∘C above preindustrial levels. Droughts with either intense severity or a long persistence could both lead to substantial impacts such as infrastructure failure and ecosystem vulnerability, and they are projected to occur more frequently and trigger intensified socioeconomic consequences with global warming. However, existing assessments targeting global droughts under 1.5 and 2.0 ∘C warming levels usually neglect the multifaceted nature of droughts and mig

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5

Latif, Shahid, and Slobodan P. Simonovic. "Parametric Vine Copula Framework in the Trivariate Probability Analysis of Compound Flooding Events." Water 14, no. 14 (2022): 2214. http://dx.doi.org/10.3390/w14142214.

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The interaction between oceanographic, meteorological, and hydrological factors can result in an extreme flooding scenario in the low-lying coastal area, called compound flooding (CF) events. For instance, rainfall and storm surge (or high river discharge) can be driven by the same meteorological forcing mechanisms, tropical or extra-tropical cyclones, resulting in a CF phenomenon. The trivariate distributional framework can significantly explain compound events’ statistical behaviour reducing the associated high-impact flood risk. Resolving heterogenous dependency of the multidimensional CF e

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6

Shiau, J. T. "Return period of bivariate distributed extreme hydrological events." Stochastic Environmental Research and Risk Assessment (SERRA) 17, no. 1-2 (2003): 42–57. http://dx.doi.org/10.1007/s00477-003-0125-9.

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7

Li, Qian, Liutong Chen, Zhengtao Yan, and Yingjun Xu. "Exploration of Copula Models Use in Risk Assessment for Freezing and Snow Events: A Case Study in Southern China." Sustainability 14, no. 5 (2022): 2568. http://dx.doi.org/10.3390/su14052568.

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Due to cold waves, low and extremely low temperatures occur every winter. Sudden cooling can cause freezing and snow disasters, which seriously affect transportation, power, safety, and other activities, resulting in serious economic losses. Based on precipitation and average temperature data from 258 national meteorological stations over the past 70 years, this study established a historical freezing and snow event data set, extracting the accumulated precipitation intensity (API) and accumulated temperature intensity (ATI). We selected the optimal distribution function and joint distribution

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8

Stamatatou, Nikoletta, Lampros Vasiliades, and Athanasios Loukas. "Bivariate Flood Frequency Analysis Using Copulas." Proceedings 2, no. 11 (2018): 635. http://dx.doi.org/10.3390/proceedings2110635.

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Flood frequency estimation for the design of hydraulic structures is usually performed as a univariate analysis of flood event magnitudes. However, recent studies show that for accurate return period estimation of the flood events, the dependence and the correlation pattern among flood attribute characteristics, such as peak discharge, volume and duration should be taken into account in a multivariate framework. The primary goal of this study is to compare univariate and joint bivariate return periods of floods that all rely on different probability concepts in Yermasoyia watershed, Cyprus. Pa

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9

Vandenberghe, S., M. J. van den Berg, B. Gräler, et al. "Joint return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation." Hydrology and Earth System Sciences Discussions 9, no. 5 (2012): 6781–828. http://dx.doi.org/10.5194/hessd-9-6781-2012.

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Abstract. Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should the joint return period be defined and applied? In this study, an overview of the state-of-the-art for defining joint return periods is given. The construction of multivariate distribution functions is done through the use of copulas, gi

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10

Requena, A. I., L. Mediero, and L. Garrote. "A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation." Hydrology and Earth System Sciences 17, no. 8 (2013): 3023–38. http://dx.doi.org/10.5194/hess-17-3023-2013.

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Abstract. A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spill

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11

Volpi, Elena. "On return period and probability of failure in hydrology." Wiley Interdisciplinary Reviews: Water 6, no. 3 (2019): e1340. http://dx.doi.org/10.1002/wat2.1340.

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12

Volpi, E., and A. Fiori. "Hydraulic structures subject to bivariate hydrological loads: Return period, design, and risk assessment." Water Resources Research 50, no. 2 (2014): 885–97. http://dx.doi.org/10.1002/2013wr014214.

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13

Mesbahzadeh, Tayyebeh, Maryam Mirakbari, Mohsen Mohseni Saravi, Farshad Soleimani Sardoo, and Nir Y. Krakauer. "Joint Modeling of Severe Dust Storm Events in Arid and Hyper Arid Regions Based on Copula Theory: A Case Study in the Yazd Province, Iran." Climate 8, no. 5 (2020): 64. http://dx.doi.org/10.3390/cli8050064.

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Natural disasters such as dust storms are random phenomena created by complicated mechanisms involving many parameters. In this study, we used copula theory for bivariate modeling of dust storms. Copula theory is a suitable method for multivariate modeling of natural disasters. We identified 40 severe dust storms, as defined by the World Meteorological Organization, during 1982–2017 in Yazd province, central Iran. We used parameters at two spatial vertical levels (near-surface and upper atmosphere) that included surface maximum wind speed, and geopotential height and vertical velocity at 500,

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14

Requena, A. I., L. Mediero, and L. Garrote. "Bivariate return period based on copulas for hydrologic dam design: comparison of theoretical and empirical approach." Hydrology and Earth System Sciences Discussions 10, no. 1 (2013): 557–96. http://dx.doi.org/10.5194/hessd-10-557-2013.

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Abstract. Hydrologic frequency analyses are usually focused on flood peaks. Multivariate analyses on flood variables have not been so exhaustively studied despite the fact that they are required to represent the full hydrograph, which is essential for designing some structures like dams. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume. An empirical bivariate return period was defined in terms of acceptable risk to the dam through the maximum water elevation reached during the routing process, in order to perform a risk assessm

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15

da Rocha Júnior, Rodrigo Lins, Fabrício Daniel dos Santos Silva, Rafaela Lisboa Costa, Heliofábio Barros Gomes, David Duarte Cavalcante Pinto, and Dirceu Luis Herdies. "Bivariate Assessment of Drought Return Periods and Frequency in Brazilian Northeast Using Joint Distribution by Copula Method." Geosciences 10, no. 4 (2020): 135. http://dx.doi.org/10.3390/geosciences10040135.

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The Northeast region of Brazil (NRB) is the most populous semiarid area in the world and is extremely susceptible to droughts. The severity and duration of these droughts depend on several factors, and they do not necessarily follow the same behavior. The aim of this work is to evaluate the frequency of droughts in the NRB and calculate the return period of each drought event using the copula technique, which integrates the duration and severity of the drought in the NRB in a joint bivariate distribution. Monthly precipitation data from 96 meteorological stations spatially distributed in the N

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16

Gabriel, Rosemary Kiama, and Yurui Fan. "Multivariate Hydrologic Risk Analysis for River Thames." Water 14, no. 3 (2022): 384. http://dx.doi.org/10.3390/w14030384.

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This study analyzed the multivariate flood risk for the river Thames at Kingston based on historical flood data from the National River Flow Archive (NRFA) website. The bivariate risk analysis framework was prepared from the joint return periods of the peak flow (m3/s) and 3-day annual maximum flow (m3/s) flood pair. A total of 137 samples of flood pairs from 1883 to 2019 were adopted for risk analysis. The multivariate return periods were characterized depending on the quantification of the bivariate flood frequency analysis of the pair through copulas methods. The unknown parameter of each c

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17

Yanmaz, A. Melih, and M. Engin Gunindi. "Assessment of overtopping reliability and benefits of a flood detention dam." Canadian Journal of Civil Engineering 35, no. 10 (2008): 1177–82. http://dx.doi.org/10.1139/l08-052.

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There is a growing tendency to assess safety levels of existing dams and to design new dams using probabilistic approaches according to project characteristics and site-specific conditions. This study is a probabilistic assessment of the overtopping reliability of a dam, which will be designed for flood detention purpose, and will compute the benefits that can be gained as a result of the implementation of this dam. In a case study, a bivariate flood frequency analysis was carried out using a five-parameter bivariate gamma distribution. A family of joint return period curves relating the runof

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18

De Luca, Davide Luciano, and Daniela Biondi. "Bivariate Return Period for Design Hyetograph and Relationship with T-Year Design Flood Peak." Water 9, no. 9 (2017): 673. http://dx.doi.org/10.3390/w9090673.

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19

Sahoo, Bibhuti Bhusan, Ramakar Jha, Anshuman Singh, and Deepak Kumar. "Bivariate low flow return period analysis in the Mahanadi River basin, India using copula." International Journal of River Basin Management 18, no. 1 (2019): 107–16. http://dx.doi.org/10.1080/15715124.2019.1576698.

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20

Chamorro, Alejandro, Tobias Houska, Shailesh Singh, and Lutz Breuer. "Projection of Droughts as Multivariate Phenomenon in the Rhine River." Water 12, no. 8 (2020): 2288. http://dx.doi.org/10.3390/w12082288.

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Drought is a complex phenomenon whose characterization is best achieved from a multivariate perspective. It is well known that it can generate adverse consequences in society. In this regard, drought duration, severity, and their interrelationship play a critical role. In a climate change scenario, drought characterization and the assessment of the changes in its pattern are essential for a proper quantification of water availability and managing strategies. The purpose of this study is to characterize hydrological droughts in the Rhine River in a multivariate perspective for the historical pe

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21

Goodarzi, Ehsan, Majid Mirzaei, and Mina Ziaei. "Evaluation of dam overtopping risk based on univariate and bivariate flood frequency analyses." Canadian Journal of Civil Engineering 39, no. 4 (2012): 374–87. http://dx.doi.org/10.1139/l2012-012.

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There is a growing tendency to assess safety of dams by mathematical and statistical methods in hydrosystem engineering. This research presents the application of risk and uncertainty analysis to dam overtopping based on univariate and bivariate flood frequency analyses by applying Gumbel logistic distribution. The bivariate frequency analyses produced six inflow hydrographs with a joint return period of 100 years. Afterward, the overtopping risk of the Doroudzan Dam was evaluated for all six inflow hydrographs by considering quantile of flood peak discharge, initial depth of water in the rese

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22

Bouabdelli, Senna, Mohamed Meddi, Ayoub Zeroual, and Ramdane Alkama. "Hydrological drought risk recurrence under climate change in the karst area of Northwestern Algeria." Journal of Water and Climate Change 11, S1 (2020): 164–88. http://dx.doi.org/10.2166/wcc.2020.207.

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Abstract This study aims to estimate hydrological drought risk using probabilistic analysis of bivariate drought characteristics to assess both past and future drought severity and duration in three basins located in the widest karst massif of northern Algeria. The procedures entail: (1) identification of extent of meteorological drought that could trigger corresponding hydrological drought through their characteristics; (2) assessment of future risk of extreme drought according to two emission scenarios of the representative concentration pathway (RCP 4.5 and 8.5); and (3) estimation of droug

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23

Kim, Yoo, Chung, and Kim. "Hydrologic Risk Assessment of Future Extreme Drought in South Korea Using Bivariate Frequency Analysis." Water 11, no. 10 (2019): 2052. http://dx.doi.org/10.3390/w11102052.

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Recently, climate change has increased the frequency of extreme weather events. In South Korea, extreme droughts are frequent and cause serious damage. To identify the risk of extreme drought, we need to calculate the hydrologic risk using probabilistic analysis methods. In particular, future hydrologic risk of extreme drought should be compared to that of the control period. Therefore, this study quantitatively assessed the future hydrologic risk of extreme drought in South Korea according to climate change scenarios based on the representative concentration pathway (RCP) 8.5. A threshold lev

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24

Li, Ning, Xueqin Liu, Wei Xie, Jidong Wu, and Peng Zhang. "The Return Period Analysis of Natural Disasters with Statistical Modeling of Bivariate Joint Probability Distribution." Risk Analysis 33, no. 1 (2012): 134–45. http://dx.doi.org/10.1111/j.1539-6924.2012.01838.x.

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25

Requena, Ana I., Ilaria Prosdocimi, Thomas R. Kjeldsen, and Luis Mediero. "A bivariate trend analysis to investigate the effect of increasing urbanisation on flood characteristics." Hydrology Research 48, no. 3 (2016): 802–21. http://dx.doi.org/10.2166/nh.2016.105.

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Flood frequency analyses are usually based on the assumption of stationarity, which might be unrealistic if changes in climate, land uses or urbanisation impact the study catchment. Moreover, most non-stationarity studies only focus on peak flows, ignoring other flood characteristics. In this study, the potential effect of increasing urbanisation on the bivariate relationship of peak flows and volumes is investigated in a case study in the northwest of England, consisting of an increasingly urbanised catchment and a nearby hydrologically and climatologically similar unchanged rural (control) c

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26

Bačová Mitková, Veronika, and Dana Halmová. "Joint modeling of flood peak discharges, volume and duration: a case study of the Danube River in Bratislava." Journal of Hydrology and Hydromechanics 62, no. 3 (2014): 186–96. http://dx.doi.org/10.2478/johh-2014-0026.

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Abstract The study is focused on the analysis and statistical evaluation of the joint probability of the occurrence of hydrological variables such as peak discharge (Q), volume (V) and duration (t). In our case study, we focus on the bivariate statistical analysis of these hydrological variables of the Danube River in Bratislava gauging station, during the period of 1876-2013. The study presents the methodology of the bivariate statistical analysis, choice of appropriate marginal distributions and appropriate copula functions in representing the joint distribution. Finally, the joint return pe

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27

Gräler, B., M. J. van den Berg, S. Vandenberghe, et al. "Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation." Hydrology and Earth System Sciences 17, no. 4 (2013): 1281–96. http://dx.doi.org/10.5194/hess-17-1281-2013.

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Abstract. Most of the hydrological and hydraulic studies refer to the notion of a return period to quantify design variables. When dealing with multiple design variables, the well-known univariate statistical analysis is no longer satisfactory, and several issues challenge the practitioner. How should one incorporate the dependence between variables? How should a multivariate return period be defined and applied in order to yield a proper design event? In this study an overview of the state of the art for estimating multivariate design events is given and the different approaches are compared.

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28

Brunner, Manuela I., Katharina Liechti, and Massimiliano Zappa. "Extremeness of recent drought events in Switzerland: dependence on variable and return period choice." Natural Hazards and Earth System Sciences 19, no. 10 (2019): 2311–23. http://dx.doi.org/10.5194/nhess-19-2311-2019.

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Abstract. The 2018 drought event had severe ecological, economic, and social impacts. How extreme was it in Switzerland? We addressed this question by looking at different types of drought, including meteorological, hydrological, agricultural, and groundwater drought, and at the two characteristics deficit and deficit duration. The analysis consisted of three main steps: (1) event identification using a threshold-level approach, (2) drought frequency analysis, and (3) comparison of the 2018 event to the severe 2003 and 2015 events. In Step 2 the variables precipitation, discharge, soil moistur

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29

Naz, Saba, Muhammad Ahsanuddin, Syed Inayatullah, Tanveer Ahmed Siddiqi, and Muhammad Imtiaz. "Copula-Based Bivariate Flood Risk Assessment on Tarbela Dam, Pakistan." Hydrology 6, no. 3 (2019): 79. http://dx.doi.org/10.3390/hydrology6030079.

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Flooding from the Indus river and its tributaries has regularly influenced the region of Pakistan. Therefore, in order to limit the misfortune brought about by these inevitable happenings, it requires taking measures to estimate the occurrence and effects of these events. The current study uses flood frequency analysis for the forecast of floods along the Indus river of Pakistan (Tarbela). The peak and volume are the characteristics of a flood that commonly depend on one another. For progressively proficient hazard investigation, a bivariate copula method is used to measure the peak and volume

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30

Neary, Vincent S., Seongho Ahn, Bibiana E. Seng, et al. "Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment." Journal of Marine Science and Engineering 8, no. 4 (2020): 289. http://dx.doi.org/10.3390/jmse8040289.

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Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave m

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31

Goodarzi, E., M. Mirzaei, L. T. Shui, and M. Ziaei. "Evaluation dam overtopping risk based on univariate and bivariate flood frequency analysis." Hydrology and Earth System Sciences Discussions 8, no. 6 (2011): 9757–96. http://dx.doi.org/10.5194/hessd-8-9757-2011.

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Abstract. There is a growing tendency to assess the safety levels of existing dams based on risk and uncertainty analysis using mathematical and statistical methods. This research presents the application of risk and uncertainty analysis to dam overtopping based on univariate and bivariate flood frequency analyses by applying Gumbel logistic distribution for the Doroudzan earth-fill dam in south of Iran. The bivariate frequency analysis resulted in six inflow hydrographs with a joint return period of 100-yr. The overtopping risks were computed for all of those hydrographs considering quantile

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32

Chang, Kook-Hyun, and Byung-Jo Yoon. "Forecasting the Currency Spot with the Trading Volume and the Trading Volume Volatility of Currency Futures in Won/Dollar FX Market." Journal of Derivatives and Quantitative Studies 18, no. 3 (2010): 1–23. http://dx.doi.org/10.1108/jdqs-03-2010-b0001.

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This paper tries to empirically investigate whether the information contained in trading volume, volume volatility of Won/Dollar currency futures may be statistically useful in forecasting currency spot return. This paper uses both the jump-diffusion GARCH model and the bivariate GARCH type BEKK model to estimate the trading volume volatility of currency futures and the volatility of currency spot, sampled daily during 1/4/2000~12/30/2009 period. According to the findings of this study, previous information contained in both trading volume and the volume volatility of Won/Dollar currency futur

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33

Li, Tianyuan, Shenglian Guo, Zhangjun Liu, Lihua Xiong, and Jiabo Yin. "Bivariate design flood quantile selection using copulas." Hydrology Research 48, no. 4 (2016): 997–1013. http://dx.doi.org/10.2166/nh.2016.049.

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Flood event consists of peak discharge and flood volume that are mutually correlated and can be described by a copula function. For a given bivariate joint distribution, a choice of design return period will lead to infinite combinations of peak discharge and flood volume. A boundary identification method is developed to define the feasible ranges of flood peak and volume suitable for combination, and two combination methods, i.e., equivalent frequency combination (EFC) method and conditional expectation combination method for estimating unique bivariate flood quantiles are also proposed. Mont

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34

Orcel, Olivier, Philippe Sergent, and François Ropert. "Trivariate copula to design coastal structures." Natural Hazards and Earth System Sciences 21, no. 1 (2021): 239–60. http://dx.doi.org/10.5194/nhess-21-239-2021.

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Abstract. Some coastal structures must be redesigned in the future due to rising sea levels caused by climate change. The design of structures subjected to the actions of waves requires an accurate estimate of the long return period of such parameters as wave height, wave period, storm surge and more specifically their joint exceedance probabilities. The simplified Defra method that is currently used in particular for European coastal structures makes it possible to directly connect the joint exceedance probabilities to the product of the univariate probabilities by means of a single factor. T

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35

Skenderi, Nagip, and Adem Dreshaj. "Influence of Macroeconomic Factors in Failure of Return of Bank Loans in Kosovo." Mediterranean Journal of Social Sciences 9, no. 5 (2018): 97–106. http://dx.doi.org/10.2478/mjss-2018-0141.

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Abstract The risk from non-payment of loans is a challenge for all the banks. Payment of the loans is a crucial issue for efficient functioning of the banking system. Loaning is one of the main uncertainties in the banking business, for loan payment can be rarely guaranteed completely. Often, a question occurs: what are the factors that influence in failure of the return of bank loan? What are the politics that must be followed to stimulate the return of bank loans? Through this research we aim to highlight the reasons of debtors in failing of loan return by studying the link of macroeconomic

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36

Stamatatou, Nikoletta, Lampros Vasiliades, and Athanasios Loukas. "The Effect of Sample Size on Bivariate Rainfall Frequency Analysis of Extreme Precipitation." Proceedings 7, no. 1 (2018): 19. http://dx.doi.org/10.3390/ecws-3-05815.

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The objective of this study is to compare univariate and joint bivariate return periods of extreme precipitation that all rely on different probability concepts in selected meteorological stations in Cyprus. Pairs of maximum rainfall depths with corresponding durations are estimated and compared using annual maximum series (AMS) for the complete period of the analysis and 30-year subsets for selected data periods. Marginal distributions of extreme precipitation are examined and used for the estimation of typical design periods. The dependence between extreme rainfall and duration is then asses

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37

Subramaniam, Srividya, Gagan Sharma, and Srishti Sehgal. "Profitability of Style based Investment Strategies: Evidence from India." Asian Journal of Finance & Accounting 9, no. 2 (2017): 1. http://dx.doi.org/10.5296/ajfa.v9i2.11456.

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In this paper, we aim to identify profitable investment styles on the Indian stock market by using various combinations of important stock pricing anomalies consisting of. size, value, volume, profitability, earnings surprises, short term and long term prior returns. Using NSE200 stocks, three different investment styles viz. univariate, independent bivariate and conditional bivariate are constructed for the period July 2005-June 2016.Results show that on an absolute return basis, bivariate strategies do not seem to outperform univariate strategies. The unifactor CAPM is able to absorb 42% of

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38

Vandenberghe, S., N. E. C. Verhoest, E. Buyse, and B. De Baets. "A stochastic design rainfall generator based on copulas and mass curves." Hydrology and Earth System Sciences Discussions 7, no. 3 (2010): 3613–48. http://dx.doi.org/10.5194/hessd-7-3613-2010.

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Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results m

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39

Vandenberghe, S., N. E. C. Verhoest, E. Buyse, and B. De Baets. "A stochastic design rainfall generator based on copulas and mass curves." Hydrology and Earth System Sciences 14, no. 12 (2010): 2429–42. http://dx.doi.org/10.5194/hess-14-2429-2010.

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Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate point-scale design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how t

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Kho, Jenniefer Y., Michael P. Gaspar, Patrick M. Kane, Sidney M. Jacoby, and Eon K. Shin. "Prognostic Variables for Patient Return-to-Work Interval Following Carpal Tunnel Release in a Workers’ Compensation Population." HAND 12, no. 3 (2016): 246–51. http://dx.doi.org/10.1177/1558944716661991.

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Background: We hypothesize that depressive and anxiety disorders, chronic pain conditions, and work-related factors are significant determinants of the time interval for return to work (RTW) in the workers’ compensation (WC) population following carpal tunnel release (CTR) surgery. Methods: We retrospectively reviewed records of all WC patients who underwent open CTR surgery over a 5-year period by 1 of 3 fellowship-trained hand surgeons. One hundred fifty-two wrists in 108 patients (64 unilateral, 44 bilateral) met the inclusion criteria. Demographic, medical, and surgical data were obtained

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Pabaghi, Zeynab, Ommolbanin Bazrafshan, Hossein Zamani, Marzieh Shekari, and Vijay P. Singh. "Bivariate Analysis of Extreme Precipitation Using Copula Functions in Arid and Semi-Arid Regions." Atmosphere 14, no. 2 (2023): 275. http://dx.doi.org/10.3390/atmos14020275.

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This study analyzed extreme precipitation events, using daily rainfall data for 1966–2015. A Mann–Kendall trend test was used to evaluate trends in extreme precipitation, copula functions were applied to compute the joint return periods of extreme events, and univariate and bivariate distributions were used to determine risk. The results showed that the decrease in consecutive wet days (CWD) was significant in the west and the northwest of Iran, while the consecutive dry days (CDD) index was increasing therein. The precipitation on more than the 90th percentile (P90) very wet days and annual n

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Najib, Mohamad Khoirun, Sri Nurdiati, and Faiqul Fikri. "Rarity of Joint Probability Between Interest and Inflation Rates in the 1998 Economic Crisis in Indonesia and Their Comparison Over Three Time Periods." Jurnal Matematika MANTIK 8, no. 1 (2022): 10–17. http://dx.doi.org/10.15642/mantik.2022.8.1.10-17.

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After more than twenty years, there has been no economic crisis as severe as 1998 based on inflation and interest rates. It is interesting to compare the conditions before and after the 1998 crisis and the economic conditions in the last decade in Indonesia. Therefore, this study aims to analyze the relationship between inflation and interest rates using a copula-based joint distribution. The joint return period of the 1998 economic crisis is estimated from this joint distribution. The results showed that the Gumbel copula is the most suitable bivariate copula to construct a joint distribution

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Yoo, Chulsang, Minkyu Park, Hyeon Jun Kim, and Changhyun Jun. "Comparison of annual maximum rainfall events of modern rain gauge data (1961–2010) and Chukwooki data (1777–1910) in Seoul, Korea." Journal of Water and Climate Change 9, no. 1 (2017): 58–73. http://dx.doi.org/10.2166/wcc.2017.110.

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Abstract In this study, the annual maximum rainfall event series were constructed and compared for both the modern flip-bucket type rainfall data, collected since 1961 (the modern data), and the old Chukwooki rainfall data, collected from 1777 to 1910 (the Chukwooki data). First, independent rainfall events were derived, by applying the same rainfall threshold of 2 mm and data collection time interval of 2 hours, to both the Chukwooki and the modern data. Annual maximum rainfall event series were then constructed, by applying Freund's bivariate exponential distribution annually. Finally, bivar

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ABID, FATHI, and NADER NAIFAR. "THE IMPACT OF STOCK RETURNS VOLATILITY ON CREDIT DEFAULT SWAP RATES: A COPULA STUDY." International Journal of Theoretical and Applied Finance 08, no. 08 (2005): 1135–55. http://dx.doi.org/10.1142/s0219024905003372.

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The aim of this paper is to study the impact of stock returns volatility of reference entities on credit default swap rates using a new dataset from the Japanese market. The majority of empirical research suggests the inadequacy of multinormal distribution and then the failure of methods based on correlation for measuring the structure of dependency. Using a copula approach, we can model the different relationships that can exist in different ranges of behavior. We study the bivariate distributions of credit default swap rates and the measure of stock return volatility estimated with GARCH (1,

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Balistrocchi, M., and B. Bacchi. "Derivation of flood frequency curves through a bivariate rainfall distribution based on copula functions: application to an urban catchment in northern Italy's climate." Hydrology Research 48, no. 3 (2017): 749–62. http://dx.doi.org/10.2166/nh.2017.109.

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The utilization of continuous approaches, namely analytical-probabilistic methods, has often been advocated for hydraulic device sizing, in order to overcome some deficiencies of the design event method. In the analytical distribution derivation, however, strong simplifying hypotheses are usually adopted. Rainfall depth and duration independency is the most unrealistic, even if it usually leads to satisfactory agreements between derived and benchmarking distributions. The reason can lie in drawbacks related to conventional assessment techniques of multivariate rainfall distributions. Copula fu

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Sarno, Lucio, Daniel L. Thornton, and Giorgio Valente. "The Empirical Failure of the Expectations Hypothesis of the Term Structure of Bond Yields." Journal of Financial and Quantitative Analysis 42, no. 1 (2007): 81–100. http://dx.doi.org/10.1017/s0022109000002192.

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AbstractThis paper tests the expectations hypothesis (EH) using U.S. monthly data for bond yields spanning the 1952–2003 sample period and ranging in maturity from one month to 10 years. We apply the Lagrange multiplier test developed by Bekaert and Hodrick (2001) and extend it to increase the test power by introducing economic variables as conditioning information and by using more than two bond yields in the model and testing the EH jointly on more than one pair of yields. While the conventional bivariate procedure provides mixed results, the more powerful testing procedures suggest rejectio

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Hung, Ngo Thai. "Return and volatility spillover across equity markets between China and Southeast Asian countries." Journal of Economics, Finance and Administrative Science 24, no. 47 (2019): 66–81. http://dx.doi.org/10.1108/jefas-10-2018-0106.

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Purpose This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia). Design/methodology/approach The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis. Findings The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the sto

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Zeng, Ning. "Monetary Stability and Stock Returns: A Bivariate Generalized Autoregressive Conditional Heteroscedasticity Modelling Study." Business and Economic Research 5, no. 2 (2015): 1. http://dx.doi.org/10.5296/ber.v5i2.7623.

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<p class="ber"><span lang="EN-GB">This paper employs a constant conditional correlation bivariate EGARCH-in-mean model to investigate interactions among the rate of inflation, stock returns and their respective volatilities. This approach is capable of accommodating all the possible causalities among the four variables simultaneously, and therefore could deliver contemporary evidence of the nexus between monetary stability and stock market. The postwar dataset of the US inflation and stock returns is divided into pre- and post- Volcker period and the estimation results show some si

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Sasongko, Leopoldus Ricky, and Bambang Susanto. "The Mean Value Theorem for Integrals Method for Estimating Two-Dimensional Renewal Functions." JTAM | Jurnal Teori dan Aplikasi Matematika 4, no. 1 (2020): 49. http://dx.doi.org/10.31764/jtam.v4i1.1831.

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An important aspect in the provision of a two-dimensional warranty is the expected number of failures of a component during the two-dimensional warranty period. The purpose of this paper is to present a new method to obtain the expected number of failures of a nonrepairable component from the two-dimensional renewal functions as the solution of two-dimensional renewal integral equations through the Mean Value Theorem for Integrals (MeVTI) method. The two-dimensional renewal integral equation involves Lu-Bhattacharyya’s bivariate Weibull model as a two-dimensional failure model. It turns out

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Naghibi, Farzaneh, and Gordon A. Fenton. "Calibration of resistance factors for geotechnical seismic design." Canadian Geotechnical Journal 56, no. 8 (2019): 1134–41. http://dx.doi.org/10.1139/cgj-2018-0433.

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The next edition of the Canadian Highway Bridge Design Code will contain a table of geotechnical resistance factors to be used for seismic design. This paper will estimate the geotechnical resistance factors for shallow foundations required to achieve various target maximum acceptable failure probabilities, which in turn may depend on the assumed design earthquake return period. The investigation will include consideration of design lifetime, uncertainty in the magnitude of the maximum lifetime earthquake event, and the uncertainty in ground properties. The results suggest resistance factors t

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