Journal of Statistical Software最新文献

spsurvey: Spatial Sampling Design and Analysis in R. spsurvey：R 中的空间抽样设计与分析。

IF 5.8 2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-18 DOI: 10.18637/jss.v105.i03

Michael Dumelle, Tom Kincaid, Anthony R Olsen, Marc Weber

{"title":"spsurvey: Spatial Sampling Design and Analysis in R.","authors":"Michael Dumelle, Tom Kincaid, Anthony R Olsen, Marc Weber","doi":"10.18637/jss.v105.i03","DOIUrl":"10.18637/jss.v105.i03","url":null,"abstract":"spsurvey is an R package for design-based statistical inference, with a focus on spatial data. spsurvey provides the generalized random-tessellation stratified (GRTS) algorithm to select spatially balanced samples via the grts() function. The grts() function flexibly accommodates several sampling design features, including stratification, varying inclusion probabilities, legacy (or historical) sites, minimum distances between sites, and two options for replacement sites. spsurvey also provides a suite of data analysis options, including categorical variable analysis (cat_analysis()), continuous variable analysis cont_analysis()), relative risk analysis (relrisk_analysis()), attributable risk analysis (attrisk_analysis()), difference in risk analysis (diffrisk_analysis()), change analysis (change_analysis()), and trend analysis (trend_analysis()). In this manuscript, we first provide background for the GRTS algorithm and the analysis approaches and then show how to implement them in spsurvey. We find that the spatially balanced GRTS algorithm yields more precise parameter estimates than simple random sampling, which ignores spatial information.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9926341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10747251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

hdpGLM: An R Package to Estimate Heterogeneous Effects in Generalized Linear Models Using Hierarchical Dirichlet Process 用层次Dirichlet过程估计广义线性模型中的异质效应的R包

2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v107.i10

Diogo Ferrari

{"title":"hdpGLM: An R Package to Estimate Heterogeneous Effects in Generalized Linear Models Using Hierarchical Dirichlet Process","authors":"Diogo Ferrari","doi":"10.18637/jss.v107.i10","DOIUrl":"https://doi.org/10.18637/jss.v107.i10","url":null,"abstract":"The existence of latent clusters with different responses to a treatment is a major concern in scientific research, as latent effect heterogeneity often emerges due to latent or unobserved features - e.g., genetic characteristics, personality traits, or hidden motivations - of the subjects. Conventional random- and fixed-effects methods cannot be applied to that heterogeneity if the group markers associated with that heterogeneity are latent or unobserved. Alternative methods that combine regression models and clustering procedures using Dirichlet process are available, but these methods are complex to implement, especially for non-linear regression models with discrete or binary outcomes. This article discusses the R package hdpGLM as a means of implementing a novel hierarchical Dirichlet process approach to estimate mixtures of generalized linear models outlined in Ferrari (2020). The methods implemented make it easy for researchers to investigate heterogeneity in the effect of treatment or background variables and identify clusters of subjects with differential effects. This package provides several features for out-of-the-box estimation and to generate numerical summaries and visualizations of the results. A comparison with other similar R packages is provided.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136367628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf. 等局部水平在R包qconf改进Q-Q地块测试波段中的应用。

IF 5.8 2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v106.i10

Eric Weine, Mary Sara McPeek, Mark Abney

{"title":"Application of Equal Local Levels to Improve Q-Q Plot Testing Bands with R Package qqconf.","authors":"Eric Weine, Mary Sara McPeek, Mark Abney","doi":"10.18637/jss.v106.i10","DOIUrl":"https://doi.org/10.18637/jss.v106.i10","url":null,"abstract":"Quantile-Quantile (Q-Q) plots are often difficult to interpret because it is unclear how large the deviation from the theoretical distribution must be to indicate a lack of fit. Most Q-Q plots could benefit from the addition of meaningful global testing bands, but the use of such bands unfortunately remains rare because of the drawbacks of current approaches and packages. These drawbacks include incorrect global Type I error rate, lack of power to detect deviations in the tails of the distribution, relatively slow computation for large data sets, and limited applicability. To solve these problems, we apply the equal local levels global testing method, which we have implemented in the R Package qqconf, a versatile tool to create Q-Q plots and probability-probability (P-P) plots in a wide variety of settings, with simultaneous testing bands rapidly created using recently-developed algorithms. qqconf can easily be used to add global testing bands to Q-Q plots made by other packages. In addition to being quick to compute, these bands have a variety of desirable properties, including accurate global levels, equal sensitivity to deviations in all parts of the null distribution (including the tails), and applicability to a range of null distributions. We illustrate the use of qqconf in several applications: assessing normality of residuals from regression, assessing accuracy of p values, and use of Q-Q plots in genome-wide association studies.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10193564/pdf/nihms-1890451.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9497381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

drda: An R Package for Dose-Response Data Analysis Using Logistic Functions 使用逻辑函数进行剂量-反应数据分析的R包

2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v106.i04

Alina Malyutina, Jing Tang, Alberto Pessia

引用次数: 2

ARCHModels.jl: Estimating ARCH Models in Julia ARCHModels。[j]: Julia中ARCH模型的估计

2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v107.i05

Simon A. Broda, Marc S. Paolella

引用次数: 0

REndo: Internal Instrumental Variables to Address Endogeneity REndo:解决内生性的内部工具变量

2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v107.i03

Raluca Gui, Markus Meierer, Patrik Schilter, René Algesheimer

引用次数: 1

netmeta: An R Package for Network Meta-Analysis Using Frequentist Methods netmeta:一个使用频率方法进行网络元分析的R包

IF 5.8 2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v106.i02

S. Balduzzi, G. Rücker, A. Nikolakopoulou, T. Papakonstantinou, G. Salanti, O. Efthimiou, G. Schwarzer

引用次数: 23

RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events RecordTest:一个基于破纪录事件分析极端事件非平稳性的R包

IF 5.8 2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v106.i05

Jorge Castillo-Mateo, A. Cebrián, J. Asín

{"title":"RecordTest: An R Package to Analyze Non-Stationarity in the Extremes Based on Record-Breaking Events","authors":"Jorge Castillo-Mateo, A. Cebrián, J. Asín","doi":"10.18637/jss.v106.i05","DOIUrl":"https://doi.org/10.18637/jss.v106.i05","url":null,"abstract":"The study of non-stationary behavior in the extremes is important to analyze data in environmental sciences, climate, finance, or sports. As an alternative to the classical extreme value theory, this analysis can be based on the study of record-breaking events. The R package RecordTest provides a useful framework for non-parametric analysis of non-stationary behavior in the extremes, based on the analysis of records. The underlying idea of all the non-parametric tools implemented in the package is to use the distribution of the record occurrence under series of independent and identically distributed continuous random variables, to analyze if the observed records are compatible with that behavior. Two families of tests are implemented. The first only requires the record times of the series, while the second includes more powerful tests that join the information from different types of records: upper and lower records in the forward and backward series. The package also offers functions that cover all the steps in this type of analysis such as data preparation, identification of the records, exploratory analysis, and complementary graphical tools. The applicability of the package is illustrated with the analysis of the effect of global warming on the extremes of the daily maximum temperature series in Zaragoza, Spain.","PeriodicalId":17237,"journal":{"name":"Journal of Statistical Software","volume":null,"pages":null},"PeriodicalIF":5.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89507792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Additive Bayesian Network Modeling with the R Package abn 基于R包的加性贝叶斯网络建模

IF 5.8 2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v105.i08

Gilles Kratzer, F. Lewis, A. Comin, M. Pittavino, R. Furrer

引用次数: 0

jumpdiff: A Python Library for Statistical Inference of Jump-Diffusion Processes in Observational or Experimental Data Sets jumpdiff:一个Python库，用于在观测或实验数据集中对跳跃扩散过程进行统计推断

IF 5.8 2区计算机科学

Journal of Statistical Software Pub Date : 2023-01-01 DOI: 10.18637/jss.v105.i04

L. R. Gorjão, D. Witthaut, P. Lind

引用次数: 3