• Asia Marketing Journal
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• v.1 no.4
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• pp.1-23
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• 1999

포지셔닝맵은 마케팅전략의 핵심인 STP전략을 세우는데 유용한 도구이나 포지셔닝맵을 그리기 위해서는 여러 가지 분석도구를 혼합하여 사용하여야 하였다. 본 논문에서는 완벽하지 않은 소비자 pick any/N자료와 상표의 특성자료를 이용하여, 세분시장을 모델 내에서 구분하고, 이들의 이상점을 찾아주고, 나아가서 시간의 흐름에 따라 이상점의 변화를 찾아주면서 포지셔닝맵을 그려주는 새로운 external 다차원척도모형을 제시하고 있다. 모델의 성과를 확인하기 위해서 차원의 변화, 세분시장변화, 상표구성의 변화 및 소비자표본의 변화를 임의로 만들어서 가상의 자료를 통해서 검증하였다. 실제로 사용해 보려면 저자의 홈페이지에서 프로그램을 다운 받을 수도 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.10-21
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• 2013

This study suggested combined filtering model to eliminate outlier travel time data in transportation information system, and it was based on Median Absolute Deviation and Voting Rule. This model applied Median Absolute Deviation (MAD) method to follow normal distribution as first filtering process. After that, Voting rule is applied to eliminate remaining outlier travel time data after Median Absolute Deviation. In Voting Rule, travel time samples are judged as outliers according to travel-time difference between sample data and mean data. Elimination or not of outliers are determined using a majority rule. In case study of national highway No. 3, combined filtering model selectively eliminated outliers only and could improve accuracy of estimated travel time.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.210-219
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• 2010

Consumers differ in both horizontally and vertically. Market segmentation aims to divide horizontally different (or heterogeneous) consumers into more similar (or homogeneous) small segments. A specific consumer, however, may differ in vertically. He (or she) may belong to a different market segment from another one where he (or she) belonged to before. In consumer panel data, the vertical difference can be observed by his (or her) choice among brand alternatives are changing over time. The consumer's vertical difference has been defined as 'dynamics'. In this research, we have developed a binary probit model with random-walk coefficients to capture the consumer's dynamics. With an application to a consumer panel data, we have examined how have the random-walk coefficients changed over time.

• The Korean Journal of Applied Statistics
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• v.3 no.2
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• pp.91-105
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• 1990

Several practical prior distributions are derived using the maximum entropy principle. Also, an interactive method for estimating a prior distribution which uses the minimum cross-entropy principle is proposed when there are many prior informations. The consistency of the prior distributions obtained by the entropy principles is discussed.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2060-2071
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• 1999

The complicate software failure system is defined to the superposition of the points of failure from several component point process. Because the likelihood function is difficulty in computing, we consider Gibbs sampler using iteration sampling based method. For each observed failure epoch, we applied to latent variables that indicates with component of the superposition mode. For model selection, we explored the posterior Bayesian criterion and the sum of relative errors for the comparison simple pattern with superposition model. A numerical example with NHPP simulated data set applies the thinning method proposed by Lewis and Shedler[25] is given, we consider Goel-Okumoto model and Weibull model with GOS, inference of parameter is studied. Using the posterior Bayesian criterion and the sum of relative errors, as we would expect, the superposition model is best on model under diffuse priors.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.363-372
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• 2016

Two-stage sample designs are commonly used for household surveys in Korea using as clusters the enumeration districts (EDs). Since clustering decomposes the population variation into within- and between-cluster variations, the sample sizes allocated in stages can affect the overall precision. Alternative clusters are often considered due to diverse reasons such as the EDs' limitation in size, being out-of-date, and in-assessibility to their household lists. In addition, the EDs are currently under development by the Statistics Korea as an joint effort toward their transition from the traditional practice to the register census from 2015. We present an approach for evaluating the difference in the precision of the mean estimators of the sets of the cluster units in between a hierachical and nested form, where the design effect is used to reflect the effect of the clustering and the sample allocation. We also demonstrate our approach using the U.S. Census counts from the year 2000 for Anne Arundel County in Maryland. Our research shows that the within-cluster variance can be significantly different for survey variables and thus the choice of cluster units and the associated sample allocation scheme should reflect the corresponding variance decomposition due to clustering.

• Journal of Korean Society for Quality Management
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• v.6 no.1
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• pp.14-17
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• 1978

In response surface experiments, a polynomial regression model is often used to fit the response surface to explore the functional relationship between a response variable and several independent variables, and to determine the optimum operating conditions, which would be desirable to control the quality of industrial products. The problem considered in this paper is that of selecting subsets of polynomial terms from a given polynomial model so as to achieve "improved" response surfaces in estimation of the response. Such improvement in fitting the response surfaces would be very helpful to determine the optimum operating conditions and to explore the functional relationship with better precision. A criterion is proposed for selection of polynomial terms and illustrated with an industrial example.

• Environmental and Resource Economics Review
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• v.31 no.1
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• pp.1-30
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• 2022

This study is to investigate consumers' acceptance and their willingness to pay for clothes made of materials with low microplastic emissions as an alternative to synthetic fibers made of plastics by applying the contingent valuation method. A nationwide web-based survey was conducted for 1,052 respondents proportional to region, age, and gender during February 2021. More than 75% of the sample expressed intentions to purchase microplastic emission-reducing clothing instead of synthetic fiber clothing, and more than 80% of them have stated their willingness to pay for additional prices. A variation of Heckman's sample selection model was adopted to estimate factors affecting respondents' intentions to pay for additional prices, in which the probit model of intentions to purchase the clothing with alternative materials was used as a sample selection equation. While respondents were sensitive to the amounts of price increases suggested in the CV scenario, they expressed high acceptance and preferences for eco-friendly materials regardless of the microplastic emission-reducing levels. Consumers in the circular economy were willing to pay for the range of 41,000 to 51,000 won for a pair of clothing made with microplastic emission-reducing materials. In addition, as the microplastic emission-reducing rate has increased from 50% to 80%, the willingness to pay estimates were also significantly increased, ranging from 41,000~50,500 to 42,000~51,700 won.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.107-114
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• 2020

Extreme value distributions have often been used for the analysis (e.g., prediction of return level) of data which are observed from natural disaster. By the extreme value theory, the block maxima asymptotically follow the generalized extreme value distribution as sample size increases; however, this may not hold in a small sample case. For solving this problem, this paper proposes the use of a log-logistic (LLG) distribution whose validity is evaluated through goodness-of-fit test and model selection. The proposed method is illustrated with data from annual maximum earthquake magnitudes of China. Here, we present the predicted return level and confidence interval according to each return period using LLG distribution.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.