Publication | Open Access
performance: An R Package for Assessment, Comparison and Testing of Statistical Models
182
Citations
8
References
2021
Year
Unknown Venue
EngineeringRegression AnalysisStatistical AnalysisProgram EvaluationR PackageData ScienceFit StatisticsPerformance AssessmentBiostatisticsStatisticsFit IndicesRegressionPerformance MetricTest DevelopmentPerformance PackageModel ComparisonStatistical ModelsEvaluation MeasureSoftware TestingSoftware MetricPerformance MeasureData Modeling
A crucial part of statistical analysis is evaluating a model's quality and fit, or performance. During analysis, especially with regression models, investigating the fit of models to data also often involves selecting the best fitting model amongst many competing models. Upon investigation, fit indices should also be reported both visually and numerically to bring readers in on the investigative effort. While functions to build and produce diagnostic plots or to compute fit statistics exist, these are located across many packages, which results in a lack of a unique and consistent approach to assess the performance of many types of models. The result is a difficult-to-navigate, unorganized ecosystem of individual packages with different syntax, making it onerous for researchers to locate and use fit indices relevant for their unique purposes. The performance package in R fills this gap by offering researchers a suite of intuitive functions with consistent syntax for computing, building, and presenting regression model fit statistics and visualizations.
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