• Title/Summary/Keyword: Traditional Statistical

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Performance Analysis of Economic VaR Estimation using Risk Neutral Probability Distributions

  • Heo, Se-Jeong;Yeo, Sung-Chil;Kang, Tae-Hun
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.757-773
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    • 2012
  • Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.

Noise Removal using Support Vector Regression in Noisy Document Images

  • Kim, Hee-Hoon;Kang, Seung-Hyo;Park, Jai-Hyun;Ha, Hyun-Ho;Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.25 no.4
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    • pp.669-680
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    • 2012
  • Noise removal of document images is a necessary step during preprocessing to recognize characters effectively because it has influences greatly on processing speed and performance for character recognition. We have considered using the spatial filters such as traditional mean filters and Gaussian filters, and wavelet transformed based methods for noise deduction in natural images. However, these methods are not effective for the noise removal of document images. In this paper, we present noise removal of document images using support vector regression. The proposed approach consists of two steps which are SVR training step and SVR test step. We construct an optimal prediction model using grid search with cross-validation in SVR training step, and then apply it to noisy images to remove noises in test step. We evaluate our SVR based method both quantitatively and qualitatively for noise removal in Korean, English and Chinese character documents, and compare it to some existing methods. Experimental results indicate that the proposed method is more effective and can get satisfactory removal results.

Sparse Design Problem in Local Linear Quasi-likelihood Estimator (국소선형 준가능도 추정량의 자료 희박성 문제 해결방안)

  • Park, Dong-Ryeon
    • The Korean Journal of Applied Statistics
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    • v.20 no.1
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    • pp.133-145
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    • 2007
  • Local linear estimator has a number of advantages over the traditional kernel estimators. The better performance near boundaries is one of them. However, local linear estimator can produce erratic result in sparse regions in the realization of the design and to solve this problem much research has been done. Local linear quasi-likelihood estimator has many common properties with local linear estimator, and it turns out that sparse design can also lead local linear quasi-likelihood estimator to erratic behavior in practice. Several methods to solve this problem are proposed and their finite sample properties are compared by the simulation study.

Functional ARCH (fARCH) for high-frequency time series: illustration (고빈도 시계열 분석을 위한 함수 변동성 fARCH(1) 모형 소개와 예시)

  • Yoon, J.E.;Kim, Jong-Min;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.30 no.6
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    • pp.983-991
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    • 2017
  • High frequency time series are now prevalent in financial data. However, models need to be further developed to suit high frequency time series that account for intraday volatilities since traditional volatility models such as ARCH and GARCH are concerned only with daily volatilities. Due to $H{\ddot{o}}rmann$ et al. (2013), functional ARCH abbreviated as fARCH is proposed to analyze intraday volatilities based on high frequency time series. This article introduces fARCH to readers that illustrate intraday volatility configuration on the KOSPI and the Hyundai motor company based on the data with one minute high frequency.

Effects of Respiratory Muscle Training on the Respiratory Function, Balance, and Activities of Daily Living in Patients with Stroke

  • Kang, Tae-Woo;Kim, Beom-Ryong
    • The Journal of Korean Physical Therapy
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    • v.30 no.2
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    • pp.58-62
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    • 2018
  • Purpose: This study evaluated the effects of respiratory muscle training on respiratory function, balance, and activities of daily living (ADL) in patients with stroke. Methods: The study included 21 patients with stroke, divided into the experimental group and control group. Both groups underwent traditional physical therapy once a day for 30 minutes, five times weekly for 6 weeks. The experimental group underwent additional respiratory muscle training once a day, five times a week during the study period. Maximal inspiratory pressure (MIP), maximal expiratory pressure (MEP), Berg balance scale (BBS), and Korean-modified Barthel index (K-MBI) were measured before and after the study period. For statistical analysis, paired t-test was used to compare the difference between the pre and post values. Independent t-test was used compare the differences between groups. Results: Both groups had significantly improved MIP, MEP, BBS, and K-MBI scores after the study period. The experimental group had significantly improved MIP, MEP, BBS, and K-MBI scores. Conclusion: These results suggest that respiratory muscle training improves respiratory function, balance, and ADL in patients with stroke.

Color Characteristic on Tongue Image of Malignant Neoplasm Patients (종양환자의 설 색상 특성에 관한 정량적 연구)

  • Eo Yun-Hye;Kim Ji-Eun;Yoo Hwa-Seung;Park Kyung-Mo
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.19 no.5
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    • pp.1437-1442
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    • 2005
  • Tongue Diagnosis is the important traditional oriental medical diagnosis method that observes not only the general physiological state but also some kinds of disease. However, manual tongue diagnosis is much influenced by surrounding illumination. Therefore, Digital Tongue Inspection System(DigiTis) is needed for the quantification of objective tongue information, In this research, Tongue images of 98 malignant Neoplasm patients and 34 normal persons were collected by Digital Tongue Inspection System. Statistical analysis of tongue images and patient data indicates that cancer group has more blue-purple components in tongue body(舌質) and yellow components in tongue coating than normal group. Also, there are a lot of rose-pink components in the cancer group of second stage and blue-purple components in the cancer group of third or fourth stage. Our study shows that tongue image is a useful index for distinction between disease and health. Furthermore we need more extended research through the additional sampling and various disease.

Wave Models and Experimental Studies of Beam-plate-beam Coupled Systems for a Mid-frequency Analysis (중주파수 대역 해석을 위한 Beam-plate-beam 연성 구조물의 웨이브 모형 연구와 시험적 규명)

  • Yoo, Ji-Woo;Thompson, D.J.;Ferguson, N.S.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.17 no.2 s.119
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    • pp.121-129
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    • 2007
  • There has been much effort to find suitable methods for structural analysis in the mid-frequency region where traditional low frequency methods have increasing uncertainties whilst statistical energy analysis is not strictly applicable. Systems consisting of relatively stiff beams coupled to flexible plates have a particularly broad mid-frequency region where the beams support only a few modes whilst the plate has a high modal density and modal overlap. A system of two parallel beams coupled to a plate is investigated based on the wave method, which is an approximate method. Muller's method is utilised for obtaining complex roots of a dispersion wave equation, which does not converge in the conventional wave method based on a simple iteration. The wave model is extended from a single-beam-plate system, to a plate with two identical beams which is modelled using a symmetric-antisymmetric technique. The important hypothesis that the coupled beam wavenumber is sufficiently smaller than the plate free wavenumber is experimentally verified. Finally, experimental results such as powers and energy ratios show the validity of the analytical wave models.

Matrix completion based adaptive sampling for measuring network delay with online support

  • Meng, Wei;Li, Laichun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.3057-3075
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    • 2020
  • End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

Analysing the Effects of Regional Factors on the Regional Variation of Obesity Rates Using the Geographically Weighted Regression (공간분석을 이용한 지역별 비만율에 영향을 미치는 요인분석)

  • Kim, Da Yang;Kwak, Jin-Mi;Seo, Eun-Won;Lee, Kwang-Soo
    • Health Policy and Management
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    • v.26 no.4
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    • pp.271-278
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    • 2016
  • Background: This study purposed to analyze the relationship between regional obesity rates and regional variables. Methods: Data was collected from the Korean Statistical Information Service (KOSIS) and Community Health Survey in 2012. The units of analysis were administrative districts such as city, county, and district. The dependent variable was the age-sex adjusted regional obesity rates. The independent variables were selected to represent four aspects of regions: health behaviour factor, psychological factor, socio-economic factor, and physical environment factor. Along with the traditional ordinary least square (OLS) regression analysis model, this study applied geographically weighted regression (GWR) analysis to calculate the regression coefficients for each region. Results: The OLS results showed that there were significant differences in regional obesity rates in high-risk drinking, walking, depression, and financial independence. The GWR results showed that the size of regression coefficients in independent variables was differed by regions. Conclusion: Our results can help in providing useful information for health policy makers. Regional characteristics should be considered when allocating health resources and developing health-related programs.

A Study on the Production Condition and Satisfaction with Knitted Jacket for the Middle-aged Women (중년 여성용 니트 재킷의 생산실태 및 만족도에 관한 연구)

  • Choi Jin-hee;Han Jin-yee
    • Journal of the Korean Society of Clothing and Textiles
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    • v.29 no.8 s.145
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    • pp.1068-1078
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    • 2005
  • The purpose of this study was to analyze the production process of 12 domestic companies that manufacture women's knitwear and the degree of satisfaction of the middle-anged women who purchase knitted Jacket. Three hundred questionnaires were distributed and a total of 276 usable data were coded for further statistical analysis including descriptive statistics (frequency and one way- ANOVA test) by using SPSSWIN 10.1. It was found that the price satisfaction of knitted jacket was low because of imported yarn and production methods(i .e., 1inking, sewing, etc.). Therefore, it is necessary to develop that domestic yam and improve production methods. Another finding ot the study demonstrated that the size of knitted jacket was a little tight for the middle-aged women on the circumstance size(i.e., bust, waist, etc.) while majority of the respondents felt that the areas such as sleeve and shoulder seemed a little bit longer than their size. It should be designed in such that the physical characteristics of knitted materials are considered when pattern is made. Clothing companies should make an effort to effort more information about the knitted jacket and develop pattern suitable for the body shape of the middle-aged women.