• Korean Journal of Applied Biomechanics
• /
• v.29 no.4
• /
• pp.255-261
• /
• 2019

Objective: The purpose of this study was to investigate differences of shock attenuation strategies between double-leg and single-leg landing on sagittal plane using statistical parametric mapping. Method: Nine healthy female professional soccer players (age: 24.0±2.5 yrs, height: 164.9±3.3 cm, weight: 55.7±6.6 kg, career: 11.2±1.4 yrs) were participated in this study. The subjects performed 10 times of double-leg and single-leg landing from the box of 30 cm height onto force plates respectively. The ground reaction force, angle, moment, angular velocity, and power of the ankle, knee, and hip joint on sagittal plane was calculated from initial contact to maximum knee flexion during landing phase. Statistical parametric mapping was used to compare the biomechanical variables of double-leg and single-leg landing of the dominant leg throughout the landing phase. Each mean difference of variables was analyzed using a paired t-test and alpha level was set to 0.05. Results: For the biomechanical variables, significantly increased vertical ground reaction force, plantarflexion moment of the ankle joint, negative ankle joint power and extension moment of the hip joint were found in single-leg landing compared to double-leg landing (p<.05). In addition, the flexion angle and angular velocity of the knee and hip joint in double-leg landing were observed significantly greater than single-leg landing, respectively (p<.05). Conclusion: These findings suggested that negative joint power and plantarflexion moment of the ankle joint can contribute to shock absorption during single-leg landing and may be the factors for preventing the musculoskeletal injuries of the lower extremity by an external force.

• The Korean Journal of Applied Statistics
• /
• v.20 no.1
• /
• pp.79-89
• /
• 2007

A test for normality introduced by Arizono and Ohta(1989) is based on fullback-Leibler discrimination information. The test statistic is derived from the discrimination information estimated using sample entropy of Vasicek(1976) and the maximum likelihood estimator of the variance. However, these estimators are biased and so it is reasonable to make use of unbiased estimators to accurately estimate the discrimination information. In this paper, Arizono-Ohta test for normality is improved. The derived test statistic is based on the bias-corrected entropy estimator and the uniformly minimum variance unbiased estimator of the variance. The properties of the improved KL test are investigated and Monte Carlo simulation is performed for power comparison.

• Communications for Statistical Applications and Methods
• /
• v.18 no.2
• /
• pp.245-255
• /
• 2011

There are two nonparametric methods that use empirical distribution functions and probability density estimators for the test of the distribution change of data. In this paper we investigate the two methods precisely and summarize the results of previous research. We assume several probability models to make a simulation study of the change point analysis and to examine the finite sample behavior of the two methods. Empirical powers are compared to verify which is better for each model.

• Journal of The Korean Astronomical Society
• /
• v.45 no.6
• /
• pp.147-156
• /
• 2012

We present a test of the emission statistics of active galactic nuclei (AGN), probing the connection between the red-noise temporal power spectra and multi-modal flux distributions known from observations. We simulate AGN lightcurves under the assumption of uniform stochastic emission processes for different power-law indices of their respective power spectra. For sufficiently shallow slopes (power-law indices (${\beta}{\leq}1$), the flux distributions (histograms) of the resulting lightcurves are approximately Gaussian. For indices corresponding to steeper slopes (${\beta}{\geq}1$), the flux distributions become multi-modal. This finding disagrees systematically with results of recent mm/radio observations. Accordingly, we conclude that the emission from AGN does not necessarily originate from uniform stochastic processes even if their power spectra suggest otherwise. Possible mechanisms include transitions between different activity states and/or the presence of multiple, spatially disconnected, emission regions.

• Communications for Statistical Applications and Methods
• /
• v.29 no.5
• /
• pp.591-601
• /
• 2022

In gene set analysis with microarray expression data, a group of genes such as a gene regulatory pathway and a signaling pathway is often tested if there exists either differentially expressed (DE) or differentially co-expressed (DC) genes between two biological conditions. Recently, a statistical test based on covariance estimation have been proposed in order to identify DC genes. In particular, covariance regularization by hard thresholding indeed improved the power of the test when the proportion of DC genes within a biological pathway is relatively small. In this article, we compare covariance thresholding methods using four different regularization penalties such as lasso, hard, smoothly clipped absolute deviation (SCAD), and minimax concave plus (MCP) penalties. In our extensive simulation studies, we found that both SCAD and MCP thresholding methods can outperform the hard thresholding method when the proportion of DC genes is extremely small and the number of genes in a biological pathway is much greater than a sample size. We also applied four thresholding methods to 3 different microarray gene expression data sets related with mutant p53 transcriptional activity, and epithelium and stroma breast cancer to compare genetic pathways identified by each method.

• The Korean Journal of Applied Statistics
• /
• v.26 no.4
• /
• pp.611-622
• /
• 2013

Mudholkar and Tian (2002) proposed an entropy-based test of fit for the inverse Gaussian distribution; however, the test can be applied to only the composite hypothesis of the inverse Gaussian distribution with an unknown location parameter. In this paper, we propose an entropy-based goodness-of-fit test for an inverse Gaussian distribution that can be applied to the composite hypothesis of the inverse Gaussian distribution as well as the simple hypothesis of the inverse Gaussian distribution with a specified location parameter. The proposed test is based on the probability integration transformation. The critical values of the test statistic estimated by simulations are presented in a tabular form. A simulation study is performed to compare the proposed test under some selected alternatives with Mudholkar and Tian (2002)'s test in terms of power. The results show that the proposed test has better power than the previous entropy-based test.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.14 no.12
• /
• pp.1311-1320
• /
• 2003

This paper proposed the estimating method of electromagnetic dosimetric reliability at in-vivo and in-vitro experiments. For more accurate consequences of these researches, we have tried to find out any correlations among output power, power density and specific absorption rate(SAR) with the results of in-vivo, in-vitro tests and SAR reports of cellular phone and PDA. In the case of in-vivo tests, the power density has close statistical correlations with SAR value and in the event of in-vitro tests, the output power has considerable statistical correlations with SAR containing duty factor. We analysed the coefficient of determination to estimate the dosimeoic uncertainty. If we use this method before evaluating techniques of measurement and analysis at both in-vivo and in-vitro experiments, we will conduct more accurate reliability test.

• The Korean Journal of Applied Statistics
• /
• v.18 no.1
• /
• pp.99-113
• /
• 2005

In this article, we propose a chi-squared test of spherical symmetry. The advantage of this test is that the test statistic and its asymptotic p-value are easy to compute. The limiting distribution of the test statistic is derived under spherical symmetry and its accuracy, in finite samples, is studied via simulation. Also, a simulation study is conducted in which the power of our test is compared with those of other tests for spherical symmetry in various alternative distributions. Finally, an illustrative example of application to a real data is provided.

• The Korean Journal of Applied Statistics
• /
• v.15 no.2
• /
• pp.355-366
• /
• 2002

Nonparametric statistical inference for the parameter of logit model were examined. Usually nonparametric approach is milder than parametric approach based on normal theory assumption. We compared the two nonparametric methods for legit model, the bootstrap and random permutation in the sense of coverage probability. Monte Carlo simulation is conducted for small sample cases. Empirical power of hypothesis test and coverage probability for confidence interval estimation were presented for simple and multiple legit model respectively. An example were also introduced.

• Communications for Statistical Applications and Methods
• /
• v.16 no.2
• /
• pp.239-347
• /
• 2009

This paper presents Kolmogorov-Smirnov, mean difference, AUROC and AR, four well known statistics that have been widely used for evaluating the discriminatory power of credit rating models. Criteria for these statistics are determined by the value of mean difference under the assumption of normality and equal standard deviation. Alternative criteria are proposed through the simulations according to various sample sizes, type II error rates, and the ratio of bads, also we suggest the meaning of statistic on the basis of discriminatory power. Finally we make a comparative study of the currently used guidelines and simulated results.