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Communications for Statistical Applications and Methods最新文献

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An alternative method for estimating lognormal means 另一种估计对数正态均值的方法
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-07-31 DOI: 10.29220/csam.2021.28.4.351
Yeil Kwon
{"title":"An alternative method for estimating lognormal means","authors":"Yeil Kwon","doi":"10.29220/csam.2021.28.4.351","DOIUrl":"https://doi.org/10.29220/csam.2021.28.4.351","url":null,"abstract":"For a probabilistic model with positively skewed data, a lognormal distribution is one of the key distributions that play a critical role. Several lognormal models can be found in various areas, such as medical science, engineering, and finance. In this paper, we propose a new estimator for a lognormal mean and depict the performance of the proposed estimator in terms of the relative mean squared error (RMSE) compared with Shen’s estimator (Shen et al. , 2006), which is considered the best estimator among the existing methods. The proposed estimator includes a tuning parameter. By finding the optimal value of the tuning parameter, we can improve the average performance of the proposed estimator over the typical range of σ 2 . The bias reduction of the proposed estimator tends to exceed the increased variance, and it results in a smaller RMSE than Shen’s estimator. A numerical study reveals that the proposed estimator has performance comparable with Shen’s estimator when σ 2 is small and exhibits a meaningful decrease in the RMSE under moderate and large σ 2 values.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44758563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Is it possible to forecast KOSPI direction using deep learning methods? 能否利用深度学习方法预测KOSPI走势?
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-07-31 DOI: 10.29220/csam.2021.28.4.329
Songa Choi, Jongwoo Song
{"title":"Is it possible to forecast KOSPI direction using deep learning methods?","authors":"Songa Choi, Jongwoo Song","doi":"10.29220/csam.2021.28.4.329","DOIUrl":"https://doi.org/10.29220/csam.2021.28.4.329","url":null,"abstract":"Deep learning methods have been developed, used in various fields, and they have shown outstanding performances in many cases. Many studies predicted a daily stock return, a classic example of time-series data, using deep learning methods. We also tried to apply deep learning methods to Korea’s stock market data. We used Korea’s stock market index (KOSPI) and several individual stocks to forecast daily returns and directions. We compared several deep learning models with other machine learning methods, including random forest and XGBoost. In regression, long short term memory (LSTM) and gated recurrent unit (GRU) models are better than other prediction models. For the classification applications, there is no clear winner. However, even the best deep learning models cannot predict significantly better than the simple base model. We believe that it is challenging to predict daily stock return data even if we use the latest deep learning methods.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42001168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
vlda: An R package for statistical visualization of multidimensional longitudinal data 一个用于多维纵向数据统计可视化的R包
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-07-31 DOI: 10.29220/csam.2021.28.4.369
Yong-Seok Choi, Leebohui, Seongwon Ryu
{"title":"vlda: An R package for statistical visualization of multidimensional longitudinal data","authors":"Yong-Seok Choi, Leebohui, Seongwon Ryu","doi":"10.29220/csam.2021.28.4.369","DOIUrl":"https://doi.org/10.29220/csam.2021.28.4.369","url":null,"abstract":"","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43144489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting movie audience with stacked generalization by combining machine learning algorithms 结合机器学习算法的叠加泛化预测电影观众
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.217
Junghoon Park, Changwon Lim
{"title":"Predicting movie audience with stacked generalization by combining machine learning algorithms","authors":"Junghoon Park, Changwon Lim","doi":"10.29220/CSAM.2021.28.3.217","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.217","url":null,"abstract":"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 o ffi ce 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.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49435379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Semi closed-form pricing autocallable ELS using Brownian Bridge 利用布朗桥对可自动调用的ELS进行半封闭式定价
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.251
Minha Lee, Jimin Hong
{"title":"Semi closed-form pricing autocallable ELS using Brownian Bridge","authors":"Minha Lee, Jimin Hong","doi":"10.29220/CSAM.2021.28.3.251","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.251","url":null,"abstract":"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 e ffi cient 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 di ff erent ways: explicit pricing formula, the Crude Monte Carlo simulation method and the Brownian Bridge technique.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44896799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Non-identifiability and testability of missing mechanisms in incomplete two-way contingency tables 不完全双向列联表中缺失机制的不可识别性和可测试性
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.307
Yousung Park, Seung Mo Oh, Tae Yeon Kwon
{"title":"Non-identifiability and testability of missing mechanisms in incomplete two-way contingency tables","authors":"Yousung Park, Seung Mo Oh, Tae Yeon Kwon","doi":"10.29220/CSAM.2021.28.3.307","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.307","url":null,"abstract":"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.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46951762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Stable activation-based regression with localizing property 具有局部化特性的基于激活的稳定回归
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.281
Jae-Kyung Shin, Jae-Hwan Jhong, J. Koo
{"title":"Stable activation-based regression with localizing property","authors":"Jae-Kyung Shin, Jae-Hwan Jhong, J. Koo","doi":"10.29220/CSAM.2021.28.3.281","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.281","url":null,"abstract":"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 coe ffi cients of the activation functions via (cid:96) 1 -penalization, through which the activation functions to be regarded as unnecessary are removed. In implementation, an e ffi cient 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.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48421069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Comparison of accuracy between LC model and 4-PFM when COVID-19 impacts mortality structure 新冠肺炎影响死亡率结构时LC模型和4-PFM的准确性比较
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.233
Jang-Suk Choi
{"title":"Comparison of accuracy between LC model and 4-PFM when COVID-19 impacts mortality structure","authors":"Jang-Suk Choi","doi":"10.29220/CSAM.2021.28.3.233","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.233","url":null,"abstract":"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","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42423195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fused inverse regression with multi-dimensional responses 多维响应的融合逆回归
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.267
Youyoung Cho, Hyoseon Hana, J. Yoo
{"title":"Fused inverse regression with multi-dimensional responses","authors":"Youyoung Cho, Hyoseon Hana, J. Yoo","doi":"10.29220/CSAM.2021.28.3.267","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.267","url":null,"abstract":"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. Su ffi cient dimension reduction provides e ff ective tools for the reduction, but there are few su ffi cient 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.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45557869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Correlation plot for a contingency table 列联表的相关图
IF 0.4
Communications for Statistical Applications and Methods Pub Date : 2021-05-31 DOI: 10.29220/CSAM.2021.28.3.295
C. Hong, Taekkyung Oh
{"title":"Correlation plot for a contingency table","authors":"C. Hong, Taekkyung Oh","doi":"10.29220/CSAM.2021.28.3.295","DOIUrl":"https://doi.org/10.29220/CSAM.2021.28.3.295","url":null,"abstract":"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 coe ffi cients for each of the two selected levels of the row and column variables. Using the correlation coe ffi cients, 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.","PeriodicalId":44931,"journal":{"name":"Communications for Statistical Applications and Methods","volume":" ","pages":""},"PeriodicalIF":0.4,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48574071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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