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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)~25권1호(2018) |수록논문 수 : 1,786
CSAM(Communications for Statistical Applications and Methods)
25권1호(2018년) 수록논문
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KCI등재

1On inference of multivariate means under ranked set sampling

저자 : ( Haresh Rochani ) , ( Daniel F Linder ) , ( Hani Samawi ) , ( Viral Panchal )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 1-13 (13 pages)

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In many studies, a researcher attempts to describe a population where units are measured for multiple outcomes, or responses. In this paper, we present an efficient procedure based on ranked set sampling to estimate and perform hypothesis testing on a multivariate mean. The method is based on ranking on an auxiliary covariate, which is assumed to be correlated with the multivariate response, in order to improve the efficiency of the estimation. We showed that the proposed estimators developed under this sampling scheme are unbiased, have smaller variance in the multivariate sense, and are asymptotically Gaussian. We also demonstrated that the efficiency of multivariate regression estimator can be improved by using Ranked set sampling. A bootstrap routine is developed in the statistical software R to perform inference when the sample size is small. We use a simulation study to investigate the performance of the method under known conditions and apply the method to the biomarker data collected in China Health and Nutrition Survey (CHNS 2009) data.

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2Use of beta-P distribution for modeling hydrologic events

저자 : ( Md. Sharwar Murshed ) , ( Yun Am Seo ) , ( Jeong-soo Park ) , ( Youngsaeng Lee

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 15-27 (13 pages)

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Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than beta-κ, Gumbel, and GEV distributions.

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3A generalized regime-switching integer-valued GARCH(1, 1) model and its volatility forecasting

저자 : ( Jiyoung Lee ) , ( Eunju Hwang )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 29-42 (14 pages)

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We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markovchain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.

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4Use of Levy distribution to analyze longitudinal data with asymmetric distribution and presence of left censored data

저자 : ( Jorge A. Achcar ) , ( Em´ılio A. Coelho-barros ) , ( Jos´e Rafael Tovar Cuevas

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 43-60 (18 pages)

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This paper considers the use of classical and Bayesian inference methods to analyze data generated by variables whose natural behavior can be modeled using asymmetric distributions in the presence of left censoring. Our approach used a L`evy distribution in the presence of left censored data and covariates. This distribution could be a good alternative to model data with asymmetric behavior in many applications as lifetime data for instance, especially in engineering applications and health research, when some observations are large in comparison to other ones and standard distributions commonly used to model asymmetry data like the exponential, Weibull or log-logistic are not appropriate to be fitted by the data. Inferences for the parameters of the proposed model under a classical inference approach are obtained using a maximum likelihood estimators (MLEs) approach and usual asymptotical normality for MLEs based on the Fisher information measure. Under a Bayesian approach, the posterior summaries of interest are obtained using standard Markov chain Monte Carlo simulation methods and available software like SAS. A numerical illustration is presented considering data of thyroglobulin levels present in a group of individuals with differentiated cancer of thyroid.

KCI등재

5Negative binomial loglinear mixed models with general random effects covariance matrix

저자 : ( Youkyung Sung ) , ( Keunbaik Lee )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 61-70 (10 pages)

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Modeling of the random effects covariance matrix in generalized linear mixed models (GLMMs) is an issue in analysis of longitudinal categorical data because the covariance matrix can be high-dimensional and its estimate must satisfy positive-definiteness. To satisfy these constraints, we consider the autoregressive and moving average Cholesky decomposition (ARMACD) to model the covariance matrix. The ARMACD creates a more flexible decomposition of the covariance matrix that provides generalized autoregressive parameters, generalized moving average parameters, and innovation variances. In this paper, we analyze longitudinal count data with overdispersion using GLMMs. We propose negative binomial loglinear mixed models to analyze longitudinal count data and we also present modeling of the random effects covariance matrix using the ARMACD. Epilepsy data are analyzed using our proposed model.

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6A note on the test for the covariance matrix under normality

저자 : ( Hyo-il Park )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 71-78 (8 pages)

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In this study, we consider the likelihood ratio test for the covariance matrix of the multivariate normal data. For this, we propose a method for obtaining null distributions of the likelihood ratio statistics by the Monte- Carlo approach when it is difficult to derive the exact null distributions theoretically. Then we compare the performance and precision of distributions obtained by the asymptotic normality and the Monte-Carlo method for the likelihood ratio test through a simulation study. Finally we discuss some interesting features related to the likelihood ratio test for the covariance matrix and the Monte-Carlo method for obtaining null distributions for the likelihood ratio statistics.

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7Independence and maximal volume of d-dimensional random convex hull

저자 : ( Won Son ) , ( Seongoh Park ) , ( Johan Lim )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 79-89 (11 pages)

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In this paper, we study the maximal property of the volume of the convex hull of d-dimensional independent random vectors. We show that the volume of the random convex hull from a multivariate location-scale family indexed by Σ is stochastically maximized in simple stochastic order when Σ is diagonal. The claim can be applied to a broad class of multivariate distributions that include skewed/unskewed multivariate t-distributions. We numerically investigate the proven stochastic relationship between the dependent and independent random convex hulls with the Gaussian random convex hull. The numerical results confirm our theoretical findings and the maximal property of the volume of the independent random convex hull.

KCI등재

8An optimal continuous type investment policy for the surplus in a risk model

저자 : ( Seung Kyoung Choi ) , ( Eui Yong Lee )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 91-97 (7 pages)

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In this paper, we show that there exists an optimal investment policy for the surplus in a risk model, in which the surplus is continuously invested to other business at a constant rate a > 0, whenever the level of the surplus exceeds a given threshold V > 0. We assign, to the risk model, two costs, the penalty per unit time while the level of the surplus being under V > 0 and the opportunity cost per unit time by keeping a unit amount of the surplus. After calculating the long-run average cost per unit time, we show that there exists an optimal investment rate a* > 0 which minimizes the long-run average cost per unit time, when the claim amount follows an exponential distribution.

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9Robustizing Kalman filters with the M-estimating functions

저자 : ( Ro Jin Pak )

발행기관 : 한국통계학회 간행물 : CSAM(Communications for Statistical Applications and Methods) 25권 1호 발행 연도 : 2018 페이지 : pp. 99-107 (9 pages)

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This article considers a robust Kalman filter from the M-estimation point of view. Pak (Journal of the Korean Statistical Society, 27, 507-514, 1998) proposed a particular M-estimating function which has the data-based shaping constants. The Kalman filter with the proposed M-estimating function is considered. The structure and the estimating algorithm of the Kalman filter accompanying the M-estimating function are mentioned. Kalman filter estimates by the proposed M-estimating function are shown to be well behaved even when data are contaminated.

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