Journal of data science : JDS最新文献_第5页

Dynamic Classification of Plasmodium vivax Malaria Recurrence: An Application of Classifying Unknown Cause of Failure in Competing Risks. 间日疟原虫疟疾复发的动态分类:未知失败原因分类在竞争风险中的应用。

Journal of data science : JDS Pub Date : 2022-01-01 Epub Date: 2021-12-09 DOI: 10.6339/21-jds1026

Yutong Liu, Feng-Chang Lin, Jessica T Lin, Quefeng Li

{"title":"Dynamic Classification of Plasmodium vivax Malaria Recurrence: An Application of Classifying Unknown Cause of Failure in Competing Risks.","authors":"Yutong Liu, Feng-Chang Lin, Jessica T Lin, Quefeng Li","doi":"10.6339/21-jds1026","DOIUrl":"https://doi.org/10.6339/21-jds1026","url":null,"abstract":"A standard competing risks set-up requires both time to event and cause of failure to be fully observable for all subjects. However, in application, the cause of failure may not always be observable, thus impeding the risk assessment. In some extreme cases, none of the causes of failure is observable. In the case of a recurrent episode of Plasmodium vivax malaria following treatment, the patient may have suffered a relapse from a previous infection or acquired a new infection from a mosquito bite. In this case, the time to relapse cannot be modeled when a competing risk, a new infection, is present. The efficacy of a treatment for preventing relapse from a previous infection may be underestimated when the true cause of infection cannot be classified. In this paper, we developed a novel method for classifying the latent cause of failure under a competing risks set-up, which uses not only time to event information but also transition likelihoods between covariates at the baseline and at the time of event occurrence. Our classifier shows superior performance under various scenarios in simulation experiments. The method was applied to Plasmodium vivax infection data to classify recurrent infections of malaria.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":" ","pages":"51-78"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9347664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40585832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The Python Package open-crypto: A Cryptocurrency Data Collector Python包open-crypto:一个加密货币数据收集器

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1059

Steffen Günther, C. Fieberg, Thorsten Poddig

引用次数: 0

Multiresolution Broad Area Search: Monitoring Spatial Characteristics of Gapless Remote Sensing Data 多分辨率广域搜索:监测无间隙遥感数据的空间特征

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1072

Laura J. Wendelberger, J. Gray, Alyson G. Wilson, R. Houborg, B. Reich

{"title":"Multiresolution Broad Area Search: Monitoring Spatial Characteristics of Gapless Remote Sensing Data","authors":"Laura J. Wendelberger, J. Gray, Alyson G. Wilson, R. Houborg, B. Reich","doi":"10.6339/22-jds1072","DOIUrl":"https://doi.org/10.6339/22-jds1072","url":null,"abstract":"Global earth monitoring aims to identify and characterize land cover change like construction as it occurs. Remote sensing makes it possible to collect large amounts of data in near real-time over vast geographic areas and is becoming available in increasingly fine temporal and spatial resolution. Many methods have been developed for data from a single pixel, but monitoring pixel-wise spectral measurements over time neglects spatial relationships, which become more important as change manifests in a greater number of pixels in higher resolution imagery compared to moderate resolution. Building on our previous robust online Bayesian monitoring (roboBayes) algorithm, we propose monitoring multiresolution signals based on a wavelet decomposition to capture spatial change coherence on several scales to detect change sites. Monitoring only a subset of relevant signals reduces the computational burden. The decomposition relies on gapless data; we use 3 m Planet Fusion Monitoring data. Simulations demonstrate the superiority of the spatial signals in multiresolution roboBayes (MR roboBayes) for detecting subtle changes compared to pixel-wise roboBayes. We use MR roboBayes to detect construction changes in two regions with distinct land cover and seasonal characteristics: Jacksonville, FL (USA) and Dubai (UAE). It achieves site detection with less than two thirds of the monitoring processes required for pixel-wise roboBayes at the same resolution.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71320759","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

Subpopulation Treatment Effect Pattern Plot (STEPP) Methods with R and Stata 亚种群处理效应模式图(STEPP)方法

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1060

S. Venturini, M. Bonetti, A. Lazar, B. Cole, Xin Victoria Wang, R. Gelber, Wai-Ki Yip

{"title":"Subpopulation Treatment Effect Pattern Plot (STEPP) Methods with R and Stata","authors":"S. Venturini, M. Bonetti, A. Lazar, B. Cole, Xin Victoria Wang, R. Gelber, Wai-Ki Yip","doi":"10.6339/22-jds1060","DOIUrl":"https://doi.org/10.6339/22-jds1060","url":null,"abstract":"We introduce the stepp packages for R and Stata that implement the subpopulation treatment effect pattern plot (STEPP) method. STEPP is a nonparametric graphical tool aimed at examining possible heterogeneous treatment effects in subpopulations defined on a continuous covariate or composite score. More pecifically, STEPP considers overlapping subpopulations defined with respect to a continuous covariate (or risk index) and it estimates a treatment effect for each subpopulation. It also produces confidence regions and tests for treatment effect heterogeneity among the subpopulations. The original method has been extended in different directions such as different survival contexts, outcome types, or more efficient procedures for identifying the overlapping subpopulations. In this paper, we also introduce a novel method to determine the number of subjects within the subpopulations by minimizing the variability of the sizes of the subpopulations generated by a specific parameter combination. We illustrate the packages using both synthetic data and publicly available data sets. The most intensive computations in R are implemented in Fortran, while the Stata version exploits the powerful Mata language.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71320531","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

The Impact of COVID-19 on Subjective Well-Being: Evidence from Twitter Data COVID-19对主观幸福感的影响:来自Twitter数据的证据

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1066

Tiziana Carpi, Airo Hino, S. Iacus, G. Porro

引用次数: 2

What Kind of Music Do You Like? A Statistical Analysis of Music Genre Popularity Over Time 你喜欢什么样的音乐?音乐类型随时间流行的统计分析

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1040

Aimée M. Petitbon, D. B. Hitchcock

引用次数: 2

Sampling-based Gaussian Mixture Regression for Big Data 基于抽样的大数据高斯混合回归

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1057

Joochul Lee, E. Schifano, Haiying Wang

引用次数: 0

A Joint Analysis for Field Goal Attempts and Percentages of Professional Basketball Players: Bayesian Nonparametric Resource 职业篮球运动员投篮命中率与投篮命中率的联合分析:贝叶斯非参数资源

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1062

Eliot Wong-Toi, Hou‐Cheng Yang, Weining Shen, Guanyu Hu

引用次数: 0

Hierarchical Ridge Regression for Incorporating Prior Information in Genomic Studies. 在基因组研究中纳入先验信息的层次岭回归。

Journal of data science : JDS Pub Date : 2022-01-01 Epub Date: 2021-12-13 DOI: 10.6339/21-jds1030

Eric S Kawaguchi, Sisi Li, Garrett M Weaver, Juan Pablo Lewinger

{"title":"Hierarchical Ridge Regression for Incorporating Prior Information in Genomic Studies.","authors":"Eric S Kawaguchi, Sisi Li, Garrett M Weaver, Juan Pablo Lewinger","doi":"10.6339/21-jds1030","DOIUrl":"10.6339/21-jds1030","url":null,"abstract":"There is a great deal of prior knowledge about gene function and regulation in the form of annotations or prior results that, if directly integrated into individual prognostic or diagnostic studies, could improve predictive performance. For example, in a study to develop a predictive model for cancer survival based on gene expression, effect sizes from previous studies or the grouping of genes based on pathways constitute such prior knowledge. However, this external information is typically only used post-analysis to aid in the interpretation of any findings. We propose a new hierarchical two-level ridge regression model that can integrate external information in the form of \"meta features\" to predict an outcome. We show that the model can be fit efficiently using cyclic coordinate descent by recasting the problem as a single-level regression model. In a simulation-based evaluation we show that the proposed method outperforms standard ridge regression and competing methods that integrate prior information, in terms of prediction performance when the meta features are informative on the mean of the features, and that there is no loss in performance when the meta features are uninformative. We demonstrate our approach with applications to the prediction of chronological age based on methylation features and breast cancer mortality based on gene expression features.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":"20 1","pages":"34-50"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10451046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accelerating Fixed-Point Algorithms in Statistics and Data Science: A State-of-Art Review 加速统计和数据科学中的定点算法:最新评述

Journal of data science : JDS Pub Date : 2022-01-01 DOI: 10.6339/22-jds1051

Bohao Tang, Nicholas C. Henderson, Ravi Varadhan

{"title":"Accelerating Fixed-Point Algorithms in Statistics and Data Science: A State-of-Art Review","authors":"Bohao Tang, Nicholas C. Henderson, Ravi Varadhan","doi":"10.6339/22-jds1051","DOIUrl":"https://doi.org/10.6339/22-jds1051","url":null,"abstract":"Fixed-point algorithms are popular in statistics and data science due to their simplicity, guaranteed convergence, and applicability to high-dimensional problems. Well-known examples include the expectation-maximization (EM) algorithm, majorization-minimization (MM), and gradient-based algorithms like gradient descent (GD) and proximal gradient descent. A characteristic weakness of these algorithms is their slow convergence. We discuss several state-of-art techniques for accelerating their convergence. We demonstrate and evaluate these techniques in terms of their efficiency and robustness in six distinct applications. Among the acceleration schemes, SQUAREM shows robust acceleration with a mean 18-fold speedup. DAAREM and restarted-Nesterov schemes also demonstrate consistently impressive accelerations. Thus, it is possible to accelerate the original fixed-point algorithm by using one of SQUAREM, DAAREM, or restarted-Nesterov acceleration schemes. We describe implementation details and software packages to facilitate the application of the acceleration schemes. We also discuss strategies for selecting a particular acceleration scheme for a given problem.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71320343","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