• Title/Summary/Keyword: Sun: statistical method

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Estimation for the Exponentiated Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang Suk-Bok;Park Sun-Mi
    • Communications for Statistical Applications and Methods
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    • 제12권3호
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    • pp.643-652
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    • 2005
  • It has been known that the exponentiated exponential distribution can be used as a possible alternative to the gamma distribution or the Weibull distribution in many situations. But the maximum likelihood method does not admit explicit solutions when the sample is multiply censored. So we derive the approximate maximum likelihood estimators for the location and scale parameters in the exponentiated exponential distribution that are explicit function of order statistics. We also compare the proposed estimators in the sense of the mean squared error for various censored samples.

Intensive numerical studies of optimal sufficient dimension reduction with singularity

  • Yoo, Jae Keun;Gwak, Da-Hae;Kim, Min-Sun
    • Communications for Statistical Applications and Methods
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    • 제24권3호
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    • pp.303-315
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    • 2017
  • Yoo (2015, Statistics and Probability Letters, 99, 109-113) derives theoretical results in an optimal sufficient dimension reduction with singular inner-product matrix. The results are promising, but Yoo (2015) only presents one simulation study. So, an evaluation of its practical usefulness is necessary based on numerical studies. This paper studies the asymptotic behaviors of Yoo (2015) through various simulation models and presents a real data example that focuses on ordinary least squares. Intensive numerical studies show that the $x^2$ test by Yoo (2015) outperforms the existing optimal sufficient dimension reduction method. The basis estimation by the former can be theoretically sub-optimal; however, there are no notable differences from that by the latter. This investigation confirms the practical usefulness of Yoo (2015).

Maximizing the Overlay of Sample Units for Two Stratified Designs by Linear Programming

  • Ryu, Jea-Bok;Kim, Sun-Woong
    • Communications for Statistical Applications and Methods
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    • 제8권3호
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    • pp.719-729
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    • 2001
  • Overlap Maximization is a sampling technique to reduce survey costs and costs associated with the survey. It was first studied by Keyfitz(1951). Ernst(1998) presented a remarkable procedure for maximizing the overlap when the sampling units can be selected for two identical stratified designs simultaneously, But the approach involves mimicking the behaviour of nonlinear function by linear function and so it is less direct, even though the stratification problem for the overlap corresponds directly to the linear programming problem. furthermore, it uses the controlled selection algorithm that repeatedly needs zero-restricted controlled roundings, which are solutions of capacitated transportation problems. In this paper we suggest a comparatively simple procedure to use linear programming in order to maximize the overlap. We show how this procedure can be implemented practically.

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The Estimation of Theoretical Semivariogram Adapting Genetic Algorithm for Kriging

  • Ryu, Je-Seon;Park, Young-Sun;Cha, Kyung-Joon
    • Communications for Statistical Applications and Methods
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    • 제11권2호
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    • pp.355-368
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    • 2004
  • In order to use Kriging, one has to estimate three parameters(nugget, sill and range) of semivariogram, which shows the relationship in the given two sites. A visual fit of the semivariogram parameters to a few standard models is widely used. But, it does not give the suitable results and not provide the automated process of Kriging. The gradient based nonlinear least squares is another choices to estimate three parameters, but it has some problems such as initial value problem. In this paper, we suggest the genetic algorithm as a compatible alternative method to solve the above mentioned problem. Finally, we estimate three parameters of semivariogram of rain-fall by adapting the genetic algorithm, compute Kriging estimate and conclude its effectiveness and compatibility.

On the Comparison of Two Non-hierarchical Log-linear Models

  • Oh, Min-Gweon;Hong, Chong-Sun;Kim, Donguk
    • Communications for Statistical Applications and Methods
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    • 제5권3호
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    • pp.847-853
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    • 1998
  • Suppose we want to compare following non-hierarchical log-linear models, $H_0:f(x, heta inTheta_a)$ vs H_1:g(x, heta inTheta_eta); for; Theta_a,;Theta_etasubsetTheta;such;that;Theta_$\alpha$/ Theta_eta$. The goodness of fit test using the likelihood ratio test statistic for comparing these models could not be acceptable. By using the polyhedrons plots of Choi and Hong (1995), we propose a method to decide a better model between two non-hierarchical log-linear models $f(x: heta inTheta_a) and g(x: heta inTheta_eta)$.

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Face recognition by PLS

  • Baek, Jang-Sun
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2003년도 추계 학술발표회 논문집
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    • pp.69-72
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    • 2003
  • The paper considers partial least squares (PLS) as a new dimension reduction technique for the feature vector to overcome the small sample size problem in face recognition. Principal component analysis (PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases show that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.

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한국어 롬바드 음성의 지속시간 연구 (A Study on the Durational Characteristics of Korean Lombard Speech)

  • 김선희
    • 대한음성학회:학술대회논문집
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    • 대한음성학회 2005년도 춘계 학술대회 발표논문집
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    • pp.21-24
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    • 2005
  • This paper presents durational characteristics of Korean Lombard speech using data, which consist of 500 Lombard utterances and 500 normal utterances of 10 speakers (5 males and 5 females). Each file was segmented and labeled manually and the duration of each segment and each word was extracted. The durational change of Lombard effect in comparison with normal speech was analyzed using a statistical method. The results show that the duration of words with Lombard effect is increased in comparison with normal style, and that the average unvoiced consonantal duration is reduced while the average vocalic duration is increased. Female speakers show a stronger tendency towards lengthening the duration in Lombard speech, but without statistical significance. Finally, this study also shows that the speakers of Lombard speech could be classified according to their different duration rate.

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통계적 특성과 신경망을 이용한 초음파 화상진단 (The Ultrasound Image Diagnosis using Statistical Characteristics and Neural Network)

  • 홍정우;김선일;이두수
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1992년도 추계학술대회
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    • pp.26-28
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    • 1992
  • Texture analysis, one of the mage processing techniques, using statistical characteristics is applied to the ultrasound images, which are then classified into each types through neural network. This is a method to be used to diagnose ultrasound images automatically and objectively. First tone kinds of texture analysis techniques proposed already are used to classify ultrasound images and compared in terms of classification rate, and then a new technique if proposed which is invariant to multiplicative gain changes and image resolution.

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단기 생산공정에 활용되는 SPC 기법의 비교 연구 (Comparison of Statistical Process Control Techniques for Short Production Run)

  • 서순근;이성재;김병태
    • 품질경영학회지
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    • 제28권2호
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    • pp.70-88
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    • 2000
  • Short runs where it is neither possible nor practical to obtain sufficient subgroups to estimate accurately the control limit are common in modem business environments. In this study, the standardized control chart, Hillier's exact method, Q chart, EWMA(Exponentially Weighted Moving Average) chart for Q statistics and EWMA chart for mean and absolute deviation among many SPC(Statistical Process Control) techniques for short runs have been reviewed and advantages and disadvantages of these techniques are discussed. The simulation experiments to compare performances of these variable charts for process mean and variations are conducted for combination of subgroup size, scale and timing of shifts of process mean an/or standard deviation. Based upon simulation results, some guidelines for practitioners to choose short run SPC techniques are recommended.

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Big Data Analysis of Weather Condition and Air Quality on Cosmetics Marketing

  • Wang, Zebin;Wu, Tong;Zhao, Xinshuang;Cheng, Shuchun;Dai, Genghui;Dai, Weihui
    • Journal of Information Technology Applications and Management
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    • 제24권3호
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    • pp.93-105
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    • 2017
  • Demands of cosmetics are affected not only by the well-known elements such as brand, price, and customer's consumption capacity, but also by some latent factors, for example, weather and air environment. Due to complexity and dynamic changes of the above factors, their influences can hardly be estimated in an accurate way by the traditional approaches such as survey and questionnaires. Through modeling and statistical analysis of big data, this article studied the impacts of weather condition and air quality on customer flow and sales of the cosmetics distributors in China, and found several hidden influencing factors. It provided a big-data based method for the analysis of unconventional factors on cosmetics marketing in the changing weather condition and air environment.