Forecasting of Univariate Time Series Using the Pattern Sequence-Based Forecasting (PSF) Algorithm R package PSF version 0.5 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) Pattern Sequence Based Forecasting (PSF) takes univariate time series data as input and assist to forecast its future values. This algorithm forecasts the behavior of time series based on similarity of pattern sequences. Initially, clustering is done with the labeling of samples from database. The labels associated with samples are then used for forecasting the future behaviour of time series data. The further technical details and references regarding PSF are discussed in Vignette. Software Imports: data.table, cluster Suggests: knitr, rmarkdown, forecast Neeraj Bokde <neerajdhanraj@gmail.com> Comprehensive R Archive Network (CRAN) Neeraj Bokde, Gualberto Asencio-Cortes and Francisco Martinez-Alvarez GPL (>= 2) 2022-05-01 application/tgz https://CRAN.R-project.org/package=PSF doi:10.32614/CRAN.package.PSF