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한국통계학회> CSAM(Communications for Statistical Applications and Methods)

CSAM(Communications for Statistical Applications and Methods) update

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  • : 한국통계학회논문집(~2011)→Communications for statistical applications and methods(2012~)

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수록범위 : 1권1호(1994)~28권3호(2021) |수록논문 수 : 1,944
CSAM(Communications for Statistical Applications and Methods)
28권3호(2021년 05월) 수록논문
최근 권호 논문
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1Predicting movie audience with stacked generalization by combining machine learning algorithms

저자 : Junghoon Park , Changwon Lim

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 217-232 (16 pages)

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The Korea film industry has matured and the number of movie-watching per capita has reached the highest level in the world. Since then, movie industry growth rate is decreasing and even the total sales of movies per year slightly decreased in 2018. The number of moviegoers is the first factor of sales in movie industry and also an important factor influencing additional sales. Thus it is important to predict the number of movie audiences. In this study, we predict the cumulative number of audiences of films using stacking, an ensemble method. Stacking is a kind of ensemble method that combines all the algorithms used in the prediction. We use box office data from Korea Film Council and web comment data from Daum Movie (www.movie.daum.net). This paper describes the process of collecting and preprocessing of explanatory variables and explains regression models used in stacking. Final stacking model outperforms in the prediction of test set in terms of RMSE.

KCI등재

2Comparison of accuracy between LC model and 4-PFM when COVID-19 impacts mortality structure

저자 : Janghoon Choi

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 233-250 (18 pages)

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This paper studies if the accuracies of mortality models (LC model vs. 4-parametric model) are aggravated if a mortality structure changes due to the impact of COVID-19. LC model (LCM) uses dimension reduction for fitting to the log mortality matrix so that the performance of the dimension reduction method may not be good when the matrix structure changes. On the other hand, 4-parametric factor model (4-PFM) is designed to use factors for fitting to log mortality data by age groups so that it would be less affected by the change of the mortality structure. In fact, the forecast accuracies of LCM are better than those of 4-PFM when life-tables are used whereas those of 4-PFM are better when the mortality structure changes. Thus this result shows that 4-PFM is more reliable in performance to the structural changes of the mortality. To support the accuracy changes of LCM the functional aspect is explained by computing eigenvalues produced by singular vector decomposition

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3Semi closed-form pricing autocallable ELS using Brownian Bridge

저자 : Minha Lee , Jimin Hong

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 251-265 (15 pages)

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This paper discusses the pricing of autocallable structured product with knock-in (KI) feature using the exit probability with the Brownian Bridge technique. The explicit pricing formula of autocallable ELS derived in the existing paper handles the part including the minimum of the Brownian motion using the inclusion-exclusion principle. This has the disadvantage that the pricing formula is complicate because of the probability with minimum value and the computational volume increases dramatically as the number of autocall chances increases. To solve this problem, we applied an effcient and robust simulation method called the Brownian Bridge technique, which provides the probability of touching the predetermined barrier when the initial and terminal values of the process following the Brownian motion in a certain interval are specified. We rewrite the existing pricing formula and provide a brief theoretical background and computational algorithm for the technique. We also provide several numerical examples computed in three different ways: explicit pricing formula, the Crude Monte Carlo simulation method and the Brownian Bridge technique.

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4Fused inverse regression with multi-dimensional responses

저자 : Youyoung Cho , Hyoseon Han , Jae Keun Yoo

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 267-279 (13 pages)

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A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

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5Stable activation-based regression with localizing property

저자 : Jae-Kyung Shin , Jae-Hwan Jhong , Ja-Yong Koo

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 281-294 (14 pages)

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In this paper, we propose an adaptive regression method based on the single-layer neural network structure. We adopt a symmetric activation function as units of the structure. The activation function has a flexibility of its form with a parametrization and has a localizing property that is useful to improve the quality of estimation. In order to provide a spatially adaptive estimator, we regularize coefficients of the activation functions via ℓ1-penalization, through which the activation functions to be regarded as unnecessary are removed. In implementation, an efficient coordinate descent algorithm is applied for the proposed estimator. To obtain the stable results of estimation, we present an initialization scheme suited for our structure. Model selection procedure based on the Akaike information criterion is described. The simulation results show that the proposed estimator performs favorably in relation to existing methods and recovers the local structure of the underlying function based on the sample.

KCI등재

6Correlation plot for a contingency table

저자 : Chong Sun Hong , Tae Gyu Oh

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 295-305 (11 pages)

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Most graphical representation methods for two-dimensional contingency tables are based on the frequencies, probabilities, association measures, and goodness-of-fit statistics. In this work, a method is proposed to represent the correlation coefficients for each of the two selected levels of the row and column variables. Using the correlation coefficients, one can obtain the vector-matrix that represents the angle corresponding to each cell. Thus, these vectors are represented as a unit circle with angles. This is called a CC plot, which is a correlation plot for a contingency table. When the CC plot is used with other graphical methods as well as statistical models, more advanced analyses including the relationship among the cells of the row or column variables could be derived.

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7Non-identifiability and testability of missing mechanisms in incomplete two-way contingency tables

저자 : Yousung Park , Seung Mo Oh , Tae Yeon Kwon

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 28권 3호 발행 연도 : 2021 페이지 : pp. 307-314 (8 pages)

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We showed that any missing mechanism is reproduced by EMAR or MNAR with equal fit for observed likelihood if there are non-negative solutions of maximum likelihood equations. This is a generalization of Molenberghs et al. (2008) and Jeon et al. (2019). Nonetheless, as MCAR becomes a nested model of MNAR, a natural question is whether or not MNAR and MCAR are testable by using the well-known three statistics, LR (Likelihood ratio), Wald, and Score test statistics. Through simulation studies, we compared these three statistics. We investigated to what extent the boundary solution affect tesing MCAR against MNAR, which is the only testable pair of missing mechanisms based on observed likelihood. We showed that all three statistics are useful as long as the boundary proximity is far from 1.

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