• Communications for Statistical Applications and Methods
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• 제28권5호
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• pp.463-475
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• 2021

Desgagné and de Micheaux (2018) proposed an alternative univariate normality test to the Jarque-Bera test. The proposed statistic is based on the sample second power skewness and kurtosis while the Jarque-Bera statistic uses sample Pearson's skewness and kurtosis that are the third and fourth standardized sample moments, respectively. In this paper, we generalize their statistic to a multivariate version based on orthogonalization or an empirical standardization of data. The proposed multivariate statistic follows chi-squared distribution approximately. A simulation study shows that the proposed statistic has good control of type I error even for a very small sample size when critical values from the approximate distribution are used. It has comparable power to the multivariate version of the Jarque-Bera test with exactly the same idea of the orthogonalization. It also shows much better power for some mixed normal alternatives.

• Communications for Statistical Applications and Methods
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• 제30권4호
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• pp.423-435
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• 2023

The Jarque and Bera (1980) statistic is one of the well known statistics to test univariate normality. It is based on the sample skewness and kurtosis which are the sample standardized third and fourth moments. Desgagné and de Micheaux (2018) proposed an alternative form of the Jarque-Bera statistic based on the sample second power skewness and kurtosis. In this paper, we generalize the statistic to a multivariate version by considering some data driven directions. They are directions given by the normalized standardized scaled residuals. The statistic is a modified multivariate version of Kim (2021), where the statistic is generalized using an empirical standardization of the scaled residuals of data. A simulation study reveals that the proposed statistic shows better power when the dimension of data is big.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1955-1962
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• 2017

Induction motors are a workhorse for the industry. The condition monitoring and fault analysis are the main concern for the engineers. The bearing is one of the vital segment of the induction machine and the condition of the whole machine is decided based on the condition of the bearing. In the present paper, the vibration signal of the bearing has been used for the analysis. The first line of action is to perform a statistical analysis of the vibration signal which gives trends in signal. To get the location of a fault in the bearing the second action is to develop an index based on Wavelet Packet Transform node energy named as Bearing Damage Index (BDI). Further, Teager-Kaiser Energy Operator (TKEO) has been calculated from higher index value to get the envelope and finally Power Spectral Density (PSD) has been applied to identify the fault frequencies. A performance index has also been developed to compare the usefulness of the proposed method with other existing methods. The result shows that the strong amplitude of fault characteristics and its side bands help to decide the type of fault present in the recorded signal obtained from the bearing.

• 천문학회지
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• 제53권2호
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• pp.49-57
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• 2020

We present numerical simulations of decaying hydrodynamic turbulence initially driven by solenoidal (divergence-free) and compressive (curl-free) drivings. Most previous numerical studies for decaying turbulence assume an isothermal equation of state (EOS). Here we use a polytropic EOS, P ∝ ρ^γ, with polytropic exponent γ ranging from 0.7 to 5/3. We mainly aim at determining the effects of γ and driving schemes on the decay law of turbulence energy, E ∝ t^-α. We additionally study probability density function (PDF) of gas density and skewness of the distribution in polytropic turbulence driven by compressive driving. Our findings are as follows. First of all, we find that even if γ does not strongly change the decay law, the driving schemes weakly change the relation; in our all simulations, turbulence decays with α ≈ 1, but compressive driving yields smaller α than solenoidal driving at the same sonic Mach number. Second, we calculate compressive and solenoidal velocity components separately and compare their decay rates in turbulence initially driven by compressive driving. We find that the former decays much faster so that it ends up having a smaller fraction than the latter. Third, the density PDF of compressively driven turbulence with γ > 1 deviates from log-normal distribution: it has a power-law tail at low density as in the case of solenoidally driven turbulence. However, as it decays, the density PDF becomes approximately log-normal. We discuss why decay rates of compressive and solenoidal velocity components are different in compressively driven turbulence and astrophysical implication of our findings.

• 한국콘텐츠학회논문지
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• 제21권11호
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• pp.320-332
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• 2021

본 연구는 국내 주식시장에서 개별종목의 주가급락위험을 과거 1년간 일별수익률의 VaR(Value-at-Risk) 통계량으로 정의하고, 주가급락위험이 기대수익률에 미치는 영향을 분석하였다. 결과는 다음과 같이 요약된다. 첫째, 전체 종목을 전월의 주가급락위험의 크기 순으로 10개의 포트폴리오로 나눈 후, 주가급락위험이 가장 높은 포트폴리오를 매수하고 가장 낮은 포트폴리오를 공매도하여 매월 구성한 무비용 포트폴리오는 월평균 -2.29%의 수익률(주가급락위험 프리미엄)을 나타낸다. 둘째, Fama-MacBeth 횡단면 회귀분석에서 기업규모, 장부가대시장가비율, 시장베타, 유동성, 최대수익률, 고유변동성, 왜도 등의 다양한 기업특성변수를 통제한 후에도 전월의 주가급락위험은 금월 수익률에 대해 유의한 음(-)의 설명력을 갖는다. 셋째, 최근 1개월 이내에 주가급락폭이 큰 종목일수록 다음 달 수익률이 더 낮다. 넷째, 전월 시장수익률의 변동성과 주가급락위험 프리미엄의 크기는 음(-)의 상관관계를 갖는다. 이러한 결과는 주가급락위험에 대해 투자자들이 과소반응하는 경향으로 인해 주가급락위험이 높은 종목일수록 주가가 고평가된다는 행태재무학적 관점에서의 가설을 지지한다.