This document describes the R package UBL that allows the use of several methods for handling utility-based learning problems. Classification and regression problems that assume non-uniform costs and/or benefits pose serious challenges to predictive analytic tasks. In the context of meteorology, finance, medicine, ecology, among many other, specific domain information concerning the preference bias of the users must be taken into account to enhance the models predictive performance. To deal with this problem, a large number of techniques was proposed by the research community for both classification and regression tasks. The main goal of UBL package is to facilitate the utility-based predictive analytic task by providing a set of methods to deal with this type of problems in the R environment. It is a versatile tool that provides mechanisms to handle both regression and classification (binary and multiclass) tasks. Moreover, UBL package allows the user to specify his domain preferences, but it also provides some automatic methods that try to infer those preference bias from the domain, considering some common known settings.
An R package for Normality in Stationary Processes
正态性是分析时间序列模型中相依数据的主要假设，正态性检验在文献中得到了广泛的研究，但这些检验的实现还很有限。\textbf{nortsTest}包执行\textit{Lobato and Velasco, Epps, Psaradakis and Vavra}和\textit{random projection}的平稳过程正态性检验。此外，该软件包还提供可视化诊断功能，用于检查多个\R软件包中最常用的时间序列模型的平稳性和正态性假设。本工作的目的是展示该软件包的功能，用模拟实例展示每个测试性能，以及该软件包在时间序列分析中的模型诊断实用程序。
ALT: A Python Package for Lightweight Feature Representation in Time Series Classification
Faculty of Engineering and Natural Sciences（工程与自然科学学院）；Tampere University（塔尔库大学）；Department of Computational Sciences（计算科学系）；Wigner Research Centre for Physics（沃尔什物理研究中心）；Faculty of Science（科学学院）；Eötvös Loránd University（欧多尼·洛朗大学）；Institute for Global Prosperity（全球繁荣研究所）；University College London（伦敦大学学院）；Department of Statistics（统计学系）
Simulation-Based Decision Making in the NFL using NFLSimulatoR
在本文中，我们介绍了一个R软件包，用于模拟播放和驱动器使用播放的数据，从国家足球联盟。模拟是通过从以前的足球赛季中逐场比赛的数据进行采样而产生的。采样过程为检查模拟所产生的任何决定或推断增加了统计上的严格性。我们强调，该软件包是特别有用的数据驱动的工具，用于评估潜在的游戏中的策略或规则的变化在联赛中。我们通过评估经常争论的$\textit{going for it}$在第四次进攻时的策略，并调查球队是否应该通过超过当前标准的传球，来证明它的实用性。
