• The Korean Journal of Applied Statistics
• /
• v.35 no.4
• /
• pp.501-515
• /
• 2022

Despite the stylized statistical features of returns of financial returns such as fat-tailed distribution and leverage effect, no stochastic volatility models that can explicitly capture these features have been presented in the existing frequentist approach. we propose an approximate parameterization of stochastic volatility models that can explicitly capture the fat-tailed distribution and leverage effect of financial returns and a maximum likelihood estimation of the model using Langrock et al. (2012)'s hidden Markov model approximation in a frequentist approach. Through extensive simulation experiments and an empirical analysis, we present the statistical evidences validating the efficacy and accuracy of proposed parameterization.

• Smart Structures and Systems
• /
• v.7 no.2
• /
• pp.133-152
• /
• 2011

System identification is a fundamental step towards the application of structural health monitoring and damage detection techniques. On this respect, the development of evolved identification strategies is a priority for obtaining reliable and repeatable baseline modal parameters of an undamaged structure to be adopted as references for future structural health assessments. The paper presents the identification of the modal parameters of the Guangzhou New Television Tower, China, using a data-driven stochastic subspace identification (SSI-data) approach complemented with an appropriate automatic mode selection strategy which proved to be successful in previous literature studies. This well-known approach is based on a clustering technique which is adopted to discriminate structural modes from spurious noise ones. The method is applied to the acceleration measurements made available within the task I of the ANCRiSST benchmark problem, which cover 24 hours of continuous monitoring of the structural response under ambient excitation. These records are then subdivided into a convenient number of data sets and the variability of modal parameter estimates with ambient temperature and mean wind velocity are pointed out. Both 10 minutes and 1 hour long records are considered for this purpose. A comparison with finite element model predictions is finally carried out, using the structural matrices provided within the benchmark, in order to check that all the structural modes contained in the considered frequency interval are effectively identified via SSI-data.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.34 no.3
• /
• pp.328-338
• /
• 1998

It is main objective of this approach to present a method to analyse stochastic design sensitivity for problems of structural dynamics with randomness in design parameters. A combination of the adjoint variable approach and the second oder perturbation method is used in the finite element approach. An alternative form of the constant functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The terminal problem of the adjoint system is solved using equivalent homogeneous equations excited by initial velocities. The numerical procedures are shown to be much more efficient when based on the fold superposition method : the generalized co-ordinates are normalized and the correlated random variables are transformed to uncorrelated variables, where as the secularities are eliminated by the fast Fourier transform of complex valued sequences. Numerical algorithms have been worked out and proved to be accurate and efficient : they codes whose element derivative matrices can be explicitly generated. The numerical results of two cases - 2-dimensional portal frame and 3/4-cylindrical shell structure - for the deterministic and stochastic sensitivity analysis illustrates in this paper.

• Korean Journal of Agricultural Science
• /
• v.48 no.1
• /
• pp.59-71
• /
• 2021

This study investigated the extent to which rice producers from the Ayeyarwaddy Region of Myanmar could improve their productivity if inputs were used efficiently in rice cultivation. To achieve this objective, simple random sampling was used to collect data from 300 rice growers in the study area. Data were analyzed with the translog stochastic frontier approach to understand the production efficiencies. The study further estimated the influencing factors that affect the efficiency levels of rice farmers. The empirical result reveals that the average technical, allocative, and economic efficiencies were at 76.11, 47.85, and 34.15%, respectively. This suggests that there is considerable room for improving rice production by better utilization of the available resources at the current level of technology. This study suggests that strenthening agricultural training programs and adoption of improved rice varieties may reduce overall inefficiencies among rice farmers in Myanmar. Factors like age, household size, education, farming experience, farm size, rice variety, training, and off-farm income have a significant impact on increasing/decreasing farmer's efficiency. Efficiency can be improved by establishing farmer field school programs to increase the scale of operations. The government should encourage young educated people to participate in paddy production and also intervene to reduce input prices and control the quality of seeds.

• Journal of Mechanical Science and Technology
• /
• v.19 no.8
• /
• pp.1582-1596
• /
• 2005

Groundwater flow and behavior have to be investigated based on heterogeneous subsurface formation since the homogeneity assumption of this formation is not valid. Over the past twenty years, stochastic approach and Monte Carlo technique have been utilized very efficiently to understand the groundwater flow behavior. However, these techniques require lots of computational and numerical efforts according to the various researchers' comments. Therefore, utilizing new techniques with much less computational efforts such as Artificial Neural Network (ANN) in the prediction of the stochastic behavior for the groundwater based on heterogeneous subsurface formation is highly appreciated. The current paper introduces the ANN technique to investigate and predict the stochastic behavior of a well draw down in a confined aquifer based on subsurface heterogeneous hydraulic conductivity. Several ANN models are developed in this research to predict the unsteady two dimensional well draw down and its stochastic characteristics in a confined aquifer. The results of this study showed that ANN method with less computational efforts was very efficiently capable of simulating and predicting the stochastic behavior of the well draw down resulted from the continuous constant pumping in the middle of a confined aquifer with subsurface heterogeneous hydraulic conductivity.

• Structural Engineering and Mechanics
• /
• v.86 no.3
• /
• pp.349-359
• /
• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• Wind and Structures
• /
• v.18 no.6
• /
• pp.693-715
• /
• 2014

Stochastic processes are used to represent phenomena in many diverse fields. Numerical simulation method is widely applied for the solution to stochastic problems of complex structures when alternative analytical methods are not applicable. In some practical applications the stochastic processes show non-Gaussian properties. When the stochastic processes deviate significantly from Gaussian, techniques for their accurate simulation must be available. The various existing simulation methods of non-Gaussian stochastic processes generally can only simulate super-Gaussian stochastic processes with the high-peak characteristics. And these methodologies are usually complicated and time consuming, not sufficiently intuitive. By revealing the inherent coupling effect of the phase and amplitude part of discrete Fourier representation of random time series on the non-Gaussian features (such as skewness and kurtosis) through theoretical analysis and simulation experiments, this paper presents a novel approach for the simulation of non-Gaussian stochastic processes with the prescribed amplitude probability density function (PDF) and power spectral density (PSD) by amplitude modulation and phase reconstruction. As compared to previous spectral representation method using phase modulation to obtain a non-Gaussian amplitude distribution, this non-Gaussian phase reconstruction strategy is more straightforward and efficient, capable of simulating both super-Gaussian and sub-Gaussian stochastic processes. Another attractive feature of the method is that the whole process can be implemented efficiently using the Fast Fourier Transform. Cases studies demonstrate the efficiency and accuracy of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.3
• /
• pp.277-288
• /
• 2014

This article reviews various state estimation methods for nonlinear systems, particularly with a perspective of a process control engineer. Nonlinear state estimation methods can be classified into the following two categories: stochastic approaches and deterministic approaches. The current review compares the Bayesian approach, which is mainly a stochastic approach, and the MHE (Moving Horizon Estimation) approach, which is mainly a deterministic approach. Though both methods are reviewed, emphasis is given to the latter as it is particularly well-suited to highly nonlinear systems with slow sampling rates, which are common in chemical process applications. Recent developments in underlying theories and supporting numerical algorithms for MHE are reviewed. Thanks to these developments, applications to large-scale and complex chemical processes are beginning to show up but they are still limited at this point owing to the high numerical complexity of the method.

• KDI Journal of Economic Policy
• /
• v.39 no.4
• /
• pp.25-50
• /
• 2017

Whereas a large variety of previous studies show mixed results regarding the relationship between public investment and economic outcome, several studies have been conducted on related issues in Korea. The present study deals with the effect of public investment in Korea on economic growth and productivity. Using administrative data, it exploits three different methodologies: the total factor productivity approach, production function approach, and stochastic frontier production function approach. The results of this study show that public investment has a statistically significant effect on economic growth. However, it contributes little to enhance productivity. It is explained that there exists inefficiency of production in the Korean economy. These findings indicate that public investment has played a central role in the direct input factor and not in indirect role in Korea. Thus, it is necessary for public investment policies to concentrate on enhancing the efficiency of the Korean economy.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.35 no.4
• /
• pp.435-447
• /
• 1999

It is main objective of this approach to present a method to analyse stochastic design sensitivity for problems of structural dynamics with randomness in design parameters. A combination of the adjoint variable approach and the second order perturbation method is used in the finite element approach. An alternative form of the constant functional that holds for all times is introduced to consider the time response of dynamic sensitivity. The terminal problem of the adjoint system is solved using equivalent homogeneous equations excited by initial velocities. The numerical procedures are shown to be much more efficient when based on the fold superposition method: the generalized co-ordinates are normalized and the correlated random variables are transformed to uncorrelated variables, whereas the secularities are eliminated by the fast Fourier transform of complex valued sequences. Numerical algorithms have been worked out and proved to be accurate and efficient : they can be readily adapted to fit into the existing finite element codes whose element derivative matrices can be explicitly generated. The numerical results of two cases -2 dimensional portal frame for the comparison with reference and 3-dimensional frame structure - for the deterministic sensitivity analysis are presented.