• Journal of the Korean Data and Information Science Society
• /
• v.9 no.2
• /
• pp.357-363
• /
• 1998

In this paper we propose a nonparametric lack of fit test based on the bootstrap method for testing the null parametric linear model by using linear smoothers. Most of existing nonparametric test statistics are based on the residuals. Our test is based on the centered bootstrap residuals. Power performance of proposed bootstrap lack of fit test is investigated via Monte carlo simulation.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.10 no.1
• /
• pp.68-77
• /
• 2003

Purpose: This study analyzed the effects of meridian massage on the muscle power, ROM, and ADL in persons with cerebral palsy. Method: A non-equivalent pre-test/post-test design was used. The data were collected from August to October, 2000 from 10 persons with cerebral palsy (a control group of 5 and an experimental group of 5). Muscle power was evaluated with the Brunnstrom-Dennen gravity test, ROM with a goniometer, and ADL with a self developed ADL scale. T-test, repeated measure ANOVA were used for statistical analysis. Result: The results are; 1. For muscle power, both time series group difference (F=10.66, p=0.000) and the total period group difference (F=72.67, p=0.000) were significant between the two groups. 2. ROM was not significantly different between the two groups. 3. For ADL, both time series group difference (F=7.09, p=0.001) and total period group difference (F=35.99, p=0.000) were significant between the two groups. Conclusion: Overall, this study shows that Meridian massage is effective for muscle power, ROM, and ADL in persons with cerebral palsy person. So it can be used to develope effective nursing programs to improve the function of motion of persons with cerebral palsy.

• Communications for Statistical Applications and Methods
• /
• v.6 no.3
• /
• pp.909-918
• /
• 1999

Arizono and Ohta(1989) studied goodness of fit test of normality using the entropy estimator proposed by Vasicek (1976) Recently van Es(1992) and Correa(1995) proposed an estimator of entropy. In this paper we propose goodness of fit test statistics for normality based on Vasicek ven Es and Correa. And we compare the power of the proposed test statistics with Kolmogorov-Smirnov Kuiper Cramer von Mises Watson Anderson-Darling and Finkelstein and Schefer statistics.

• Journal of Power System Engineering
• /
• v.17 no.4
• /
• pp.86-93
• /
• 2013

This paper deals with the effects of driving force and material properties on statistical distribution of fatigue crack growth rate (FCGR) for the friction stir welded joints of Al 7075-T651 aluminum plate. In this work, the statistical probability distribution of fatigue crack growth rate was analyzed by using our previous constant stress intensity factor range controlled fatigue crack growth test data. As far as this study are concerned, the statistical probability distribution of fatigue crack growth rate for the friction stir welded (FSWed) joints was found to evaluate the variability of fatigue crack growth rate for base metal (BM), heat affected zone (HAZ) and weld metal (WM) specimens. The probability distribution of fatigue crack growth rate for FSWed joints was found to follow well log-normal distribution. The shape parameter of BM and HAZ was decreased with increasing the driving force, however, the shape parameter of WM was decreased and increased with increasing the driving force. The scale parameter of BM, HAZ and WM was increased with the driving force.

• Journal of the Korean Statistical Society
• /
• v.27 no.3
• /
• pp.305-318
• /
• 1998

Smoothing tests based on an L$_2$ error between a truncated courier series estimator and a true function have shown good powers for a wide class of alternatives, These tests have the same form of the Neyman smooth test whose performance depends on the selected order, a basis, the farm of estimators. We construct flexible data driven Neyman smooth tests by changing a basis, combining model selection criteria and different series estimators. A simulation study shows that the generalized Neyman smooth test with the best basis provides good power for a wider class of alternatives compared with other data driven Neyman smooth tests based on a fixed form of estimator, a fixed basis and a fixed criterion.

• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.101-114
• /
• 1995

In this paper we consider the multiple unit root tests both for the regular and seasonal unit roots based on the Lagrange Multiplier(LM) principle. Unlike Li(1991)'s method, by plugging the restricted maximum likelihood estimates of the nuisance parameters in the model, we propose a Lagrange multiplier test which does not depend on the existence of the nuisance parameters. The asymptotic distribution of the proposed statistic is derived and empirical percentiles of the test statistic for selected seasonal periods are provided. The power and size of the test statistic for examined for finite samples through a Monte Carlo simularion.

• Communications for Statistical Applications and Methods
• /
• v.13 no.3
• /
• pp.607-619
• /
• 2006

We consider the problem of testing the existence of change in mean and estimating the change-point when the data are from the normal distribution. A change-point estimator using the likelihood ratio test statistic, Gombay and Horvath (1990) test statistic, and nonparametric change-point estimator using Carlstein (1988) empirical distribution are studied when there exists one change-point in the mean. A power study is done to compare the change test statistics. And a comparison study of change-point estimators for estimation capability is done via simulations with S-plus software.

• Communications for Statistical Applications and Methods
• /
• v.16 no.1
• /
• pp.75-83
• /
• 2009

Parallelism tests are proposed for slope in the simple linear regression models. In this paper, we suggest the parametric test using HSD testing method (Tukey,1953) and distribution-free test using Kruskal-wallis (1952) for more than three slopes. Monte Carlo simulation study is adapted to compare the power of the proposed methods with Wilks' Lambda multivariate procedure.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.11
• /
• pp.1545-1550
• /
• 2014

Fault detection and diagnosis (FDD) of photovoltaic (PV) power systems is one of significant techniques for reducing economic loss due to abnormality occurred in PV modules. This paper presents a new FDD method against PV power systems by using statistical comparison. This comparative approach includes deviation signals between the outputs of two neighboring PV modules. We first define a binary hypothesis testing under such deviation and make use of a generalized likelihood ratio testing (GLRT) theory to derive its FDD algorithm. Additionally, a recursive computational mechanism for our proposed FDD algorithm is presented for improving a computational effectiveness in practice. We carry out a real-time experiment to test reliability of the proposed FDD algorithm by utilizing a lab based PV test-bed system.

• Communications for Statistical Applications and Methods
• /
• v.9 no.2
• /
• pp.389-399
• /
• 2002

In order to examine whether the difference between two point estimates of population proportions is statistically significant, data analysts use two techniques. The first is to explore the overlap between two associated confidence intervals. Second method is to test the significance which is introduced at most statistical textbooks under the common assumptions of consistency, asymptotic normality, and asymptotic independence of the estimates. Under the null hypothesis which is two population proportions are equal, the pooled estimator of population proportion is preferred as a point estimator since two independent random samples are considered to be collected from one population. Hence as an alternative method, we could obtain another confidence interval of the difference of the population proportions with using the pooled estimate. We conclude that, among three methods, the overlapped method is under-estimated, and the difference of the population proportions method is over-estimated on the basis of the proposed method.