Journal of the Korean Statistical Society最新文献_第4页

Disseminating massive frequency tables by masking aggregated cell frequencies 通过掩盖小区汇总频率传播海量频率表

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-30 DOI: 10.1007/s42952-023-00248-x

Min-Jeong Park, Hang J. Kim, Sunghoon Kwon

引用次数: 0

Use of ridge calibration method in predicting election results 使用脊校准法预测选举结果

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-23 DOI: 10.1007/s42952-023-00254-z

Yohan Lim, Mingue Park

引用次数: 0

Asymptotic of the number of false change points of the fused lasso signal approximator 融合套索信号近似器错误变化点数量的渐近线

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-18 DOI: 10.1007/s42952-023-00250-3

Donghyeon Yu, Johan Lim, Won Son

{"title":"Asymptotic of the number of false change points of the fused lasso signal approximator","authors":"Donghyeon Yu, Johan Lim, Won Son","doi":"10.1007/s42952-023-00250-3","DOIUrl":"https://doi.org/10.1007/s42952-023-00250-3","url":null,"abstract":"It is well-known that the fused lasso signal approximator (FLSA) is inconsistent in change point detection under the presence of staircase blocks in true mean values. The existing studies focus on modifying the FLSA model to remedy this inconsistency. However, the inconsistency of the FLSA does not severely degrade the performance in change point detection if the FLSA can identify all true change points and the estimated change points set is sufficiently close to the true change points set. In this study, we investigate some asymptotic properties of the FLSA under the assumption of the noise level (sigma _n = o(n log n)). To be specific, we show that all the falsely segmented blocks are sub-blocks of true staircase blocks if the noise level is sufficiently low and a tuning parameter is chosen appropriately. In addition, each false change point of the optimal FLSA estimate can be associated with a vertex of a concave majorant or a convex minorant of a discrete Brownian bridge. Based on these results, we derive an asymptotic distribution of the number of false change points and provide numerical examples supporting the theoretical results.","PeriodicalId":49992,"journal":{"name":"Journal of the Korean Statistical Society","volume":"10 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139499555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Large sample properties of maximum likelihood estimator using moving extremes ranked set sampling 使用移动极值排序集抽样的最大似然估计器的大样本特性

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-13 DOI: 10.1007/s42952-023-00251-2

Han Wang, Wangxue Chen, Bingjie Li

引用次数: 0

Logistic regression models for elastic shape of curves based on tangent representations 基于切线表示法的曲线弹性形状逻辑回归模型

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-12 DOI: 10.1007/s42952-023-00252-1

Tae-Young Heo, Joon Myoung Lee, Myung Hun Woo, Hyeongseok Lee, Min Ho Cho

引用次数: 0

Byzantine-resilient decentralized network learning 拜占庭式弹性分散网络学习

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-10 DOI: 10.1007/s42952-023-00249-w

Yaohong Yang, Lei Wang

引用次数: 0

Sequential online monitoring for autoregressive time series of counts 自回归计数时间序列的连续在线监测

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2024-01-02 DOI: 10.1007/s42952-023-00247-y

引用次数: 0

Return prediction by machine learning for the Korean stock market 通过机器学习预测韩国股票市场的回报率

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2023-12-20 DOI: 10.1007/s42952-023-00245-0

Wonwoo Choi, Seongho Jang, Sanghee Kim, Chayoung Park, Sunyoung Park, Seongjoo Song

{"title":"Return prediction by machine learning for the Korean stock market","authors":"Wonwoo Choi, Seongho Jang, Sanghee Kim, Chayoung Park, Sunyoung Park, Seongjoo Song","doi":"10.1007/s42952-023-00245-0","DOIUrl":"https://doi.org/10.1007/s42952-023-00245-0","url":null,"abstract":"In this study, we aim to forecast monthly stock returns and analyze factors influencing stock prices in the Korean stock market. To find a model that maximizes the cumulative return of the portfolio of stocks with high predicted returns, we use machine learning models such as linear models, tree-based models, neural networks, and learning to rank algorithms. We employ a novel validation metric which we call the Cumulative net Return of a Portfolio with top 10% predicted return (CRP10) for tuning hyperparameters to increase the cumulative return of the selected portfolio. CRP10 tends to provide higher cumulative returns compared to out-of-sample R-squared as a validation metric with the data that we used. Our findings indicate that Light Gradient Boosting Machine (LightGBM) and Gradient Boosted Regression Trees (GBRT) demonstrate better performance than other models when we apply a single model for the entire test period. We also take the strategy of changing the model on a yearly basis by assessing the best model annually and observed that it did not outperform the approach of using a single model such as LightGBM or GBRT for the entire period.","PeriodicalId":49992,"journal":{"name":"Journal of the Korean Statistical Society","volume":"65 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138816752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatially integrated estimator of finite population total by integrating data from two independent surveys using spatial information 利用空间信息整合来自两个独立调查的数据，对有限人口总数进行空间整合估算

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2023-12-19 DOI: 10.1007/s42952-023-00244-1

Nobin Chandra Paul, Anil Rai, Tauqueer Ahmad, Ankur Biswas, Prachi Misra Sahoo

{"title":"Spatially integrated estimator of finite population total by integrating data from two independent surveys using spatial information","authors":"Nobin Chandra Paul, Anil Rai, Tauqueer Ahmad, Ankur Biswas, Prachi Misra Sahoo","doi":"10.1007/s42952-023-00244-1","DOIUrl":"https://doi.org/10.1007/s42952-023-00244-1","url":null,"abstract":"A major goal of survey sampling is finite population inference. In recent years, large-scale survey programs have encountered many practical challenges which include higher data collection cost, increasing non-response rate, increasing demand for disaggregated level statistics and desire for timely estimates. Data integration is a new field of research that provides a timely solution to these above-mentioned challenges by integrating data from multiple surveys. Now, it is possible to develop a framework that can efficiently combine information from several surveys to obtain more precise estimates of population parameters. In many surveys, parameters of interest are often spatial in nature, which means, the relationship between the study variable and covariates varies across all locations in the study area and this situation is referred as spatial non-stationarity. Hence, there is a need of a sampling methodology that can efficiently tackle this spatial non-stationarity problem and can be able to integrate this spatially referenced data to get more detailed information. In this study, a Geographically Weighted Spatially Integrated (GWSI) estimator of finite population total was developed by integrating data from two independent surveys using spatial information. The statistical properties of the proposed spatially integrated estimator were then evaluated empirically through a spatial simulation study. Three different spatial populations were generated having high spatial autocorrelation. The proposed spatially integrated estimator performed better than usual design-based estimator under all three populations. Furthermore, a Spatial Proportionate Bootstrap (SPB) method was developed for variance estimation of the proposed spatially integrated estimator.","PeriodicalId":49992,"journal":{"name":"Journal of the Korean Statistical Society","volume":"15 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138744869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Statistical integration of allele frequencies from several organizations 统计整合多个组织的等位基因频率

IF 0.6 4区数学

Journal of the Korean Statistical Society Pub Date : 2023-12-18 DOI: 10.1007/s42952-023-00243-2

Su Jin Jeong, Hyo-jung Lee, Soong Deok Lee, Su Jeong Park, Seung Hwan Lee, Jae Won Lee

{"title":"Statistical integration of allele frequencies from several organizations","authors":"Su Jin Jeong, Hyo-jung Lee, Soong Deok Lee, Su Jeong Park, Seung Hwan Lee, Jae Won Lee","doi":"10.1007/s42952-023-00243-2","DOIUrl":"https://doi.org/10.1007/s42952-023-00243-2","url":null,"abstract":"Genetic evidence, especially evidence based on short tandem repeats, is of paramount importance for human identification in forensic inferences. In recent years, the identification of kinship using DNA evidence has drawn much attention in various fields. In particular, it is employed, using a criminal database, to confirm blood relations in forensics. The interpretation of the likelihood ratio when identifying an individual or a relationship depends on the allele frequencies that are used, and thus, it is crucial to obtain an accurate estimate of allele frequency. Each organization such as Supreme Prosecutors’ Office and Korean National Police Agency in Korea provides different statistical interpretations due to differing estimations of the allele frequency, which can lead to confusion in forensic identification. Therefore, it is very important to estimate allele frequency accurately, and doing so requires a certain amount of information. However, simply using a weighted average for each allele frequency may not be sufficient to determine biological independence. In this study, we propose a new statistical method for estimating allele frequency by integrating the data obtained from several organizations, and we analyze biological independence and differences in allele frequency relative to the weighted average of allele frequencies in various subgroups. Finally, our proposed method is illustrated using real data from 576 Korean individuals.","PeriodicalId":49992,"journal":{"name":"Journal of the Korean Statistical Society","volume":"21 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138717017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0