• Journal of the Korean Statistical Society
• /
• v.30 no.3
• /
• pp.407-418
• /
• 2001

Buhlmann(1944) established the validity of the block bootstrap proposed by Kunsch when it is applied to p-dimensional $\alpha$-mixing dependent sequence. But his result requires a rather restrictive condition on p in the sense that p is entangled with dependence structure. We address that such restriction on p(or complication of dependence structure with p) could be removed completely when the underlying dependence structure is replace by more weakly dependent structure such as ø-mixing.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.1
• /
• pp.104-111
• /
• 1997

Accounting for the additional damages come out from non-proportional loading path effect, material damage according to crystal structure dependence was studied. Microscopic observations of damaged material by SEM(Scanning Electron Microscope) showed crystal structure dependence. Biaxial in-phase loaded specimens showed the slips of same direction, which pararell each other, but biaxial 90.deg. out-of-phase loaded specimens showed multiply crossed slips. S. H. Doong and D. F. Socie reported that wavy/planar or planar slip material showed the increase in the cyclic hardening level during non-proportional cycling. From these results, the additional hardening and non-proportional loading effects were related with slip mechanism, and the slip mechanism was related with crystal structure. In the present study, a damage mechanism which accounts for the non-proportional loading effect from crystal structure dependence was considered and applied to A17075-T651.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.6
• /
• pp.1477-1488
• /
• 2013

In this study, we analyze the dependence structure of KOSPI and NYSE indices based on a two-step estimation procedure. In the rst step, we adopt ARMA-GARCH models with Gaussian mixture innovations for marginal processes. In the second step, time-varying copula parameters are estimated. By using these, we measure the dependence between the two returns with Kendall's tau and Spearman's rho. The two dependence measures for various copulas are illustrated.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.97-97
• /
• 2021

Hydrometeorological variables contain highly complex system for temporal revolution and it is quite challenging to illustrate the system with a temporal linear and nonlinear models. In recent years, deep learning algorithms have been developed and a number of studies has focused to model the complex hydrometeorological system with deep learning models. In the current study, we investigated the temporal structure inside deep learning models for the hydrometeorological variables such as streamflow and climate indices. The results present a quite striking such that each hidden unit of the deep learning model presents different dependence structure and when the number of hidden units meet a proper boundary, it reaches the best model performance. This indicates that the deep dependence structure of deep learning models can be used to model selection or investigating whether the constructed model setup present efficient or not.

• Journal of applied mathematics & informatics
• /
• v.5 no.2
• /
• pp.553-564
• /
• 1998

In this paper we introduce a new concept of more weakly quadrant dependence of hitting times of stochastic processes. This concept is weaker than the more positively quadrant dependence of hitting times of stochastic processes. This concept is weaker than the more positively quadrant dependence and it is closed under some statistical operations of weakly positive quadrant dependence(WPQD) ordering.

• Communications for Statistical Applications and Methods
• /
• v.21 no.5
• /
• pp.445-459
• /
• 2014

This paper investigates the dependence structure of Korean financial markets (stock, foreign exchange (FX) rates and bond) using copula-GARCH and dynamic conditional correlation (DCC) models. We examine GJR-GARCH with skewed elliptical distributions and four copulas (Gaussian, Student's t, Clayton and Gumbel) to model dependence among returns, and then employ DCC model to describe system-wide correlation dynamics. We analyze the daily returns of KOSPI, FX (WON/USD) and KRX bond index (Gross Price Index) from $2^{nd}$ May 2006 to $30^{th}$ June 2014 with 2,063 observations. Empirical result shows that there is significant asymmetry and fat-tail of individual return, and strong tail-dependence among returns, especially between KOSPI and FX returns, during the 2008 Global Financial Crisis period. Focused only on recent 30 months, we find that the correlation between stock and bond markets shows dramatic increase, and system-wide correlation wanders around zero, which possibly indicates market tranquility from a systemic perspective.

• Environmental and Resource Economics Review
• /
• v.29 no.2
• /
• pp.145-170
• /
• 2020

This study analyzes the dependence structure between energy (crude oil, natural gas, coal) prices and economic (real and financial) uncertainty. Summary of the results of the dependence structure between energy prices and economic uncertainty analysis is as follows. First, the results of model selection show that the BB7 copula model for the pair of crude oil price and economic uncertainty, the Joe copula model for the pair of natural gas price and economic uncertainty, and the Clayton copula model for the pair of coal price and economic uncertainty were chosen. Second, looking at the dependency structure, it showed that the pair of energy (crude oil, natural gas, coal) prices and real market uncertainty show positive dependence. Whereas, the only pair of financial market uncertainty-crude oil price shows positive dependency. In particular, crude oil price was found to have the greatest dependence on economic uncertainty. Third, looking at the results of tail dependency, the pair of real market uncertainty-crude oil price and pair of real market uncertainty-natural gas price have an asymmetric relationship with the upper tail dependency. It can be seen that the only pair of financial market uncertainty-crude oil represents asymmetric relationships with the upper tail dependencies. In other words, combinations with asymmetric relationships have shown strong dependence when negative extreme events occur. On the other hand, tail dependence between economic uncertainty and coal price be not found.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.3
• /
• pp.421-427
• /
• 2013

The dependence between wind speeds in multiple wind sites has a considerable impact on the reliability of power systems containing wind energy. This paper presents a new method to generate dependent wind speed time series (WSTS) based on copulas theory. The basic feature of the method lies in separating multivariate WSTS into dependence structure and univariate time series. The dependence structure is modeled through the use of copulas, which, unlike the cross-correlation matrix, give a complete description of the joint distribution. An autoregressive moving average (ARMA) model is applied to represent univariate time series of wind speed. The proposed model is illustrated using wind data from two sites in Canada. The IEEE Reliability Test System (IEEE-RTS) is used to examine the proposed model and the impact of wind speed dependence between different wind regimes on the generation system reliability. The results confirm that the wind speed dependence has a negative effect on the generation system reliability.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.5
• /
• pp.1225-1239
• /
• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• Journal of Information Technology Services
• /
• v.18 no.4
• /
• pp.171-190
• /
• 2019

This study comparatively analyzes the cases of CDMA (Code Division Multiple Access) and WIPI (Wireless Internet Platform for Interoperability) to find out the success and failure factors of technology policies in the field of mobile communication industry. For this purpose, the two cases are analyzed through a new analysis framework, which is made by combining System of Innovation with a range of variables derived from precedent studies, such as external environment, institutions, technological system, governance structure, and interactions of actors. The results of analysis show that in the CDMA case, the following factors led to success ; Korea made good use of the external opportunities in the early stage of digital communication technology and adopted a suitable governance structure for the technological system. Main actors in Innovation System had strong will for success and engaged in cooperative interaction. For the WIPI, however, the timing of technology policy was inappropriate and a unsuitable governance structure for technological system was chosen because of path dependence. The Innovation System failded to respond efficiently to the situation where conflicts among actors had intensified, US trade pressure had increased and innovative smartphones emerged. The results of this study provide the practical implications for the success of technology policy; namely it is important to choose a governance structure that suits the external environment and characteristics of technology and to activate cooperative interactions among actors in Innovation System.