• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.269-284
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• 2020

This study compares two teaching methods in an introductory statistics course at a large state university. The first method is the traditional lecture-based approach. The second method implements a flipped classroom that incorporates the recommendations of the American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. We compare these two methods, based on student performance, illustrate the procedures of the flipped pedagogy, and discuss the impact of aligning our course to current guidelines for teaching statistics at the college level. Results show that students in the flipped class performed better than students in traditional delivery. Student questionnaire responses also indicate that students in flipped delivery aligned with the GAISE recommendations have built a productive mindset in statistics.

• Journal of the Korean School Mathematics Society
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• v.8 no.2
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• pp.167-181
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• 2005

Statistics is based on a data, therefore a practical use of suitable data is important in teaching statistics. But, most teachers feel always that there is seldom data that students can understand easily. In this study, we presented a teaching method of statistics education that can elevate student's participation and interest in their statistics class using a web-based data collection program and MS Excel software. Also, the presented teaching method may apply extending to various part of statistics education.

• Journal of the Korean Statistical Society
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• v.27 no.1
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• pp.91-100
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• 1998

A method of estimating probability density using regression tools is presented here. It is based on equal-length binning and locally weighted approximate likelihood for bin counts. The method is particularly useful for densities with bounded supports, where it automatically corrects edge effects without using boundary kernels.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.273-282
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• 2008

An essential aspect of music is structure. Beran (2004) introduced a method of comparing piano plays via circular statistics based on the fact that there is circular structure in music. We expand the application of this method to a pair of two pop songs and discuss the possibility of applying it to detecting musical plagiarism. Circular statistics provides an objective view point comparing the musical works.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.325-335
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• 2002

In this paper we introduce some adaptive M-estimators using selector statistics to estimate the center of symmetric and continuous underlying distributions. This selector statistics is based on the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying distributions. In this paper, we use the functions of sample quantiles as selector statistics and determine the suitable quantile points based on maximizing the distance index to discriminate distributions under consideration. In Monte Carlo study, this robust estimation method works pretty good in wide range of underlying distributions.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.25-35
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• 1997

Most of speech analysis methods developed up to date are based on second order statistics, and one of the biggest drawback of these methods is that they show dramatical performance degradation in noisy environments. On the contrary, the methods using higher order statistics(HOS), which has the property of suppressing Gaussian noise, enable robust feature extraction in noisy environments. In this paper we propose a text-independent speaker identification system using higher order statistics and compare its performance with that using the conventional second-order-statistics-based method in both white and colored noise environments. The proposed speaker identification system is based on the vector quantization approach, and employs HOS-based voiced/unvoiced detector in order to extract feature parameters for voiced speech only, which has non-Gaussian distribution and is known to contain most of speaker-specific characteristics. Experimental results using 50 speaker's database show that higher-order-statistics-based method gives a better identificaiton performance than the conventional second-order-statistics-based method in noisy environments.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.467-475
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• 2015

Accurate demand forecasting is a crucial component in revenue management(RM). The booking data of departed flights is used to forecast the demand for future departing flights; however, some booking requests that were denied were omitted in the departed flights data. Denied booking requests can be interpreted as censored in statistics. Thus, unconstraining demand is an important issue to forecast the true demands of future flights. Several unconstraining methods have been introduced and a method based on expectation maximization is considered superior. In this study, we propose a new unconstraining method based on a regression model that can entertain such censored data. Through a simulation study, the performance of the proposed method was evaluated with two representative unconstraining methods widely used in RM.

• Wind and Structures
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• v.34 no.6
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.481-492
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• 2017

This paper investigates a convergence rate of a test statistics given by two scale sampling method based on $A\ddot{i}t$-Sahalia and Jacod (Annals of Statistics, 37, 184-222, 2009). This statistics tests for longitudinal data having the existence of long memory dependence driven by fractional Brownian motion with Hurst parameter $H{\in}(1/2,\;1)$. We obtain an upper bound in the Kolmogorov distance for normal approximation of this test statistic. As a main tool for our works, the recent results in Nourdin and Peccati (Probability Theory and Related Fields, 145, 75-118, 2009; Annals of Probability, 37, 2231-2261, 2009) will be used. These results are obtained by employing techniques based on the combination between Malliavin calculus and Stein's method for normal approximation.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.261-270
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• 2002

Recently, the demand of the Intelligent Transportation System(ITS) has been increased to a large extent, and a real-time traffic information service based on the internet system became very important. When ITS companies carry out real-time traffic services, they find some traffic data missing, and use the conventional method of reconstructing missing values by calculating average time trend. However, the method is found unsatisfactory, so that we develop a new method based the spatial and spatial-temporal models. A cross-validation technique shows that the spatial-temporal model outperforms the others.