2 10 14 https://repository.horizon.ac.id/files/original/fed21f0d7646577ffe77c205d0ce2988.pdf f5edec3fd4e60125d9af97cbc3bafa75 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 103 Tahun 2022 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v103 Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource scikit-mobility: A Python Library for the Analysis, Generation, and Risk Assessment of Mobility Data Subject The topic of the resource : data science, human mobility, mobility analysis, spatio-temporal analysis, big data, network science, data mining, Python, mathematical modeling, migration models, privacy Description An account of the resource The last decade has witnessed the emergence of massive mobility datasets, such as tracks generated by GPS devices, call detail records, and geo-tagged posts from social media platforms. These datasets have fostered a vast scientific production on various applications of mobility analysis, ranging from computational epidemiology to urban planning and transportation engineering. A strand of literature addresses data cleaning issues related to raw spatiotemporal trajectories, while the second line of research focuses on discovering the statistical “laws” that govern human movements. A significant effort has also been put on designing algorithms to generate synthetic trajectories able to reproduce, realistically, the laws of human mobility. Last but not least, a line of research addresses the crucial problem of privacy, proposing techniques to perform the re-identification of individuals in a database. A view on state-of-the-art cannot avoid noticing that there is no statistical software that can support scientists and practitioners with all the aspects mentioned above of mobility data analysis. In this paper, we propose scikit-mobility, a Python library that has the ambition of providing an environment to reproduce existing research, analyze mobility data, and simulate human mobility habits. scikit-mobility is efficient and easy to use as it extends pandas, a popular Python library for data analysis. Moreover, scikit-mobility provides the user with many functionalities, from visualizing trajectories to generating synthetic data, from analyzing statistical patterns to assessing the privacy risk related to the analysis of mobility datasets. Creator An entity primarily responsible for making the resource Luca Pappalardo Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v103i04 Publisher An entity responsible for making the resource available ISTI-CNR Date A point or period of time associated with an event in the lifecycle of the resource July 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/08f1f3b6deb80e73fa3324dbf2ca89ae.pdf 8fa1e59595bc963421ddc0a0f9746101 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 103 Tahun 2022 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v103 Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource evgam: An R Package for Generalized Additive Extreme Value Models Subject The topic of the resource : generalized extreme value distribution, generalized Pareto distribution, point process, generalized additive model, Laplace’s method, R Description An account of the resource This article introduces the R package evgam. The package provides functions for fitting extreme value distributions. These include the generalized extreme value and generalized Pareto distributions. The former can also be fitted through a point process representation. Package evgam supports quantile regression via the asymmetric Laplace distribution, which can be useful for estimating high thresholds, sometimes used to discriminate between extreme and non-extreme values. The main addition of package evgam is to let extreme value distribution parameters have generalized additive model forms, the smoothness of which can be objectively estimated using Laplace’s method. Illustrative examples fitting various distributions with various specifications are given. These include daily precipitation accumulations for part of Colorado, US, used to illustrate spatial models, and daily maximum temperatures for Fort Collins, Colorado, US, used to illustrate temporal models Creator An entity primarily responsible for making the resource Benjamin D. Youngman Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v103i03 Publisher An entity responsible for making the resource available University of Exeter Date A point or period of time associated with an event in the lifecycle of the resource July 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/64ba36e80033f5882e50b02a2caebfc2.pdf 71693303c274ac5cbd50f56b99b3d60a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 103 Tahun 2022 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v103 Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource stringi: Fast and Portable Character String Processing in R Subject The topic of the resource , character strings, text, ICU, Unicode, regular expressions, data cleansing, natural language processing, R. Description An account of the resource Effective processing of character strings is required at various stages of data analysis pipelines: from data cleansing and preparation, through information extraction, to report generation. Pattern searching, string collation and sorting, normalization, transliteration, and formatting are ubiquitous in text mining, natural language processing, and bioinformatics. This paper discusses and demonstrates how and why stringi, a mature R package for fast and portable handling of string data based on ICU (International Components for Unicode), should be included in each statistician’s or data scientist’s repertoire to complement their numerical computing and data wrangling skills Creator An entity primarily responsible for making the resource Marek Gagolewski Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v103i02 Publisher An entity responsible for making the resource available Deakin University Polish Academy of Sciences Date A point or period of time associated with an event in the lifecycle of the resource July 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/e3a0fea85827a12ce7837c89b0ffbe45.pdf 7518381eb281235c1ec3dd3b8bd98222 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOLUME 103 Tahun 2022 Source A related resource from which the described resource is derived https://www.jstatsoft.org/issue/view/v103 Date A point or period of time associated with an event in the lifecycle of the resource 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource modelsummary: Data and Model Summaries in R Subject The topic of the resource : tables, data summary, model summary, crosstab, regression table, coefficient plot, R Description An account of the resource modelsummary is a package to summarize data and statistical models in R. It supports over one hundred types of models out-of-the-box, and allows users to report the results of those models side-by-side in a table, or in coefficient plots. It makes it easy to execute common tasks such as computing robust standard errors, adding significance stars, and manipulating coefficient and model labels. Beyond model summaries, the package also includes a suite of tools to produce highly flexible data summary tables, such as dataset overviews, correlation matrices, (multi-level) cross-tabulations, and balance tables (also known as “Table 1”). The appearance of the tables produced by modelsummary can be customized using external packages such as kableExtra, gt, flextable, or huxtable; the plots can be customized using ggplot2. Tables can be exported to many output formats, including HTML, LATEX, Text/Markdown, Microsoft Word, Powerpoint, Excel, RTF, PDF, and image files. Tables and plots can be embedded seamlessly in rmarkdown, knitr, or Sweave dynamic documents. The modelsummary package is designed to be simple, robust, modular, and extensible. Creator An entity primarily responsible for making the resource Vincent Arel-Bundock Source A related resource from which the described resource is derived https://www.jstatsoft.org/article/view/v103i01 Publisher An entity responsible for making the resource available Université de Montréal Date A point or period of time associated with an event in the lifecycle of the resource July 2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text