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forecast - Forecasting Functions for Time Series and Linear Models

Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.

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forecastforecastingopenblascpp

20.62 score 1.2k stars 1.4k dependents 27k scripts 405k downloads

distributional - Vectorised Probability Distributions

Vectorised distribution objects with tools for manipulating, visualising, and using probability distributions. Designed to allow model prediction outputs to return distributions rather than their parameters, allowing users to directly interact with predictive distributions in a data-oriented workflow. In addition to providing generic replacements for p/d/q/r functions, other useful statistics can be computed including means, variances, intervals, and highest density regions.

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probability-distributionstatisticsvctrs

16.07 score 113 stars 485 dependents 1.6k scripts 485k downloads

tsibble - Tidy Temporal Data Frames and Tools

Provides a 'tbl_ts' class (the 'tsibble') for temporal data in an data- and model-oriented format. The 'tsibble' provides tools to easily manipulate and analyse temporal data, such as filling in time gaps and aggregating over calendar periods.

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14.78 score 548 stars 44 dependents 5.2k scripts 19k downloads

fable - Forecasting Models for Tidy Time Series

Provides a collection of commonly used univariate and multivariate time series forecasting models including automatically selected exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA) models. These models work within the 'fable' framework provided by the 'fabletools' package, which provides the tools to evaluate, visualise, and combine models in a workflow consistent with the tidyverse.

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forecastingcpp

13.48 score 592 stars 7 dependents 2.4k scripts 11k downloads

fabletools - Core Tools for Packages in the 'fable' Framework

Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.

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12.95 score 98 stars 24 dependents 614 scripts 14k downloads

feasts - Feature Extraction and Statistics for Time Series

Provides a collection of features, decomposition methods, statistical summaries and graphics functions for the analysing tidy time series data. The package name 'feasts' is an acronym comprising of its key features: Feature Extraction And Statistics for Time Series.

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12.49 score 310 stars 9 dependents 1.9k scripts 12k downloads

tsfeatures - Time Series Feature Extraction

Methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.

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feature-extractiontime-seriescpp

12.25 score 263 stars 22 dependents 366 scripts 14k downloads

rticles - Article Formats for R Markdown

A suite of custom R Markdown formats and templates for authoring journal articles and conference submissions.

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articlejournalpaperrmarkdown

11.83 score 1.5k stars 3 dependents 160 scripts 9.3k downloads

vitae - Curriculum Vitae for R Markdown

Provides templates and functions to simplify the production and maintenance of curriculum vitae.

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cvozunconf18resumeunconf

11.41 score 1.3k stars 805 scripts 1.2k downloads

hdrcde - Highest Density Regions and Conditional Density Estimation

Computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate,and multimodal regression.

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11.08 score 27 stars 170 dependents 180 scripts 14k downloads

icons - Easily Insert SVG Icons into R Outputs

Provides tools to download, style, and insert scalable vector graphics (SVG) icons into R output, such as 'R Markdown' and 'Quarto' documents, 'Shiny' apps, 'gt' tables, and 'ggplot2' visualisations via the 'ggicons' package. Bundles popular icon libraries, such as 'Font Awesome' (<https://fontawesome.com>), 'Academicons' (<https://jpswalsh.github.io/academicons/>), and 'Material Design Icons' (<https://fonts.google.com/icons>), which are downloaded on demand to keep the package small, or build a custom icon set from any folder of local SVG files. Icon appearance, such as size, colour, and position, can be customised.

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fontawesomeicon-libraryozunconf17unconfweb-icons

10.34 score 315 stars 2 dependents 720 scripts 506 downloads

ggtime - Grammar of Graphics and Plot Helpers for Time Series Visualization

Extends the capabilities of 'ggplot2' by providing grammatical elements and plot helpers designed for visualizing temporal patterns. The package implements a grammar of temporal graphics, which leverages calendar structures to highlight changes over time. The package also provides plot helper functions to quickly produce commonly used time series graphics, including time plots, season plots, and seasonal sub-series plots.

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9.26 score 29 stars 10 dependents 186 scripts 15k downloads

hts - Hierarchical and Grouped Time Series

Provides methods for analysing and forecasting hierarchical and grouped time series. The available forecast methods include bottom-up, top-down, optimal combination reconciliation (Hyndman et al. 2011) <doi:10.1016/j.csda.2011.03.006>, and trace minimization reconciliation (Wickramasuriya et al. 2018) <doi:10.1080/01621459.2018.1448825>.

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forecastshtscpp

9.18 score 113 stars 5 dependents 224 scripts 2.7k downloads

fpp3 - Data for "Forecasting: Principles and Practice" (3rd Edition)

All data sets required for the examples and exercises in the book "Forecasting: principles and practice" by Rob J Hyndman and George Athanasopoulos <https://OTexts.com/fpp3/>. All packages required to run the examples are also loaded. Additional data sets not used in the book are also included.

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dataforecasting

8.89 score 157 stars 3.2k scripts 7.7k downloads

fpp2 - Data for "Forecasting: Principles and Practice" (2nd Edition)

All data sets required for the examples and exercises in the book "Forecasting: principles and practice" (2nd ed, 2018) by Rob J Hyndman and George Athanasopoulos <https://otexts.com/fpp2/>. All packages required to run the examples are also loaded.

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dataforecasting

8.86 score 109 stars 1 dependents 2.3k scripts 6.3k downloads

demography - Forecasting Mortality, Fertility, Migration and Population Data

Functions for demographic analysis including lifetable calculations; Lee-Carter modelling; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting.

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actuarialdemographyforecasting

8.56 score 78 stars 6 dependents 297 scripts 3.5k downloads

fma - Data Sets from "Forecasting: Methods and Applications" by Makridakis, Wheelwright & Hyndman (1998)

All data sets from "Forecasting: methods and applications" by Makridakis, Wheelwright & Hyndman (Wiley, 3rd ed., 1998) <https://robjhyndman.com/forecasting/>.

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8.47 score 19 stars 2 dependents 372 scripts 4.6k downloads

tsibbledata - Diverse Datasets for 'tsibble'

Provides diverse datasets in the 'tsibble' data structure. These datasets are useful for learning and demonstrating how tidy temporal data can tidied, visualised, and forecasted.

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datasettsibble

8.43 score 27 stars 2 dependents 1.0k scripts 6.5k downloads

binb - 'binb' is not 'Beamer'

A collection of 'LaTeX' styles using 'Beamer' customization for pdf-based presentation slides in 'RMarkdown'. At present it contains 'RMarkdown' adaptations of the LaTeX themes 'Metropolis' (formerly 'mtheme') theme by Matthias Vogelgesang and others (now included in 'TeXLive'), the 'IQSS' them by Ista Zahn (which is included here), and the 'Monash' theme by Rob J Hyndman. Additional (free) fonts may be needed: 'Metropolis' prefers 'Fira', and 'IQSS' requires 'Libertinus'.

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beamerbeamer-presentationbeamer-thememarkdownpdfrmarkdownrmarkdown-beamer

8.14 score 192 stars 2 dependents 507 downloads

conformalForecast - Conformal Prediction Methods for Multistep-Ahead Time Series Forecasting

Methods and tools for performing multistep-ahead time series forecasting using conformal prediction methods including classical conformal prediction, adaptive conformal prediction, conformal PID (Proportional-Integral-Derivative) control, and autocorrelated multistep-ahead conformal prediction. The methods were described by Wang and Hyndman (2024) <doi:10.48550/arXiv.2410.13115>.

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8.07 score 43 stars 1 dependents 65 scripts 395 downloads

cricketdata - International Cricket Data

Data on international and other major cricket matches from ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>. This package provides some functions to download the data into tibbles ready for analysis.

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cricketcricket-dataozunconf17unconf

7.94 score 91 stars 107 scripts 531 downloads

sugrrants - Supporting Graphs for Analysing Time Series

Provides 'ggplot2' graphics for analysing time series data. It aims to fit into the 'tidyverse' and grammar of graphics framework for handling temporal data.

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statistical-graphicstime-series

7.85 score 81 stars 2 dependents 290 scripts 543 downloads

stR - Seasonal Trend Decomposition Using Regression

Methods for decomposing seasonal data: STR (a Seasonal-Trend time series decomposition procedure based on Regression) and Robust STR. In some ways, STR is similar to Ridge Regression and Robust STR can be related to LASSO. They allow for multiple seasonal components, multiple linear covariates with constant, flexible and seasonal influence. Seasonal patterns (for both seasonal components and seasonal covariates) can be fractional and flexible over time; moreover they can be either strictly periodic or have a more complex topology. The methods provide confidence intervals for the estimated components. The methods can also be used for forecasting.

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7.79 score 9 stars 1 dependents 2.3k scripts 672 downloads

weird - Functions and Data Sets for "That's Weird: Anomaly Detection Using R" by Rob J Hyndman

All functions and data sets required for the examples in the book Hyndman (2026) "That's Weird: Anomaly Detection Using R" <https://OTexts.com/weird/>. All packages needed to run the examples are also loaded.

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7.77 score 31 stars 45 scripts 428 downloads

bfast - Breaks for Additive Season and Trend

Decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt changes within the trend and seasonal components. 'BFAST' can be used to analyze different types of satellite image time series and can be applied to other disciplines dealing with seasonal or non-seasonal time series, such as hydrology, climatology, and econometrics. The algorithm can be extended to label detected changes with information on the parameters of the fitted piecewise linear models. 'BFAST' monitoring functionality is described in Verbesselt et al. (2010) <doi:10.1016/j.rse.2009.08.014>. 'BFAST monitor' provides functionality to detect disturbance in near real-time based on 'BFAST'- type models, and is described in Verbesselt et al. (2012) <doi:10.1016/j.rse.2012.02.022>. 'BFAST Lite' approach is a flexible approach that handles missing data without interpolation, and will be described in an upcoming paper. Furthermore, different models can now be used to fit the time series data and detect structural changes (breaks).

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cpp

7.75 score 54 stars 1 dependents 204 scripts 1.1k downloads

vital - Tidy Analysis Tools for Mortality, Fertility, Migration and Population Data

Analysing vital statistics based on tools consistent with the tidyverse. Tools are provided for data visualization, life table calculations, computing net migration numbers, Lee-Carter modelling; functional data modelling and forecasting.

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7.71 score 32 stars 30 scripts 310 downloads

gratis - Generating Time Series with Diverse and Controllable Characteristics

Generates synthetic time series based on various univariate time series models including MAR and ARIMA processes. Kang, Y., Hyndman, R.J., Li, F.(2020) <doi:10.1002/sam.11461>.

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data-generationmixture-autoregressivestatistical-computingtime-series

7.55 score 78 stars 45 scripts 494 downloads

expsmooth - Data Sets from "Forecasting with Exponential Smoothing"

Data sets from the book "Forecasting with exponential smoothing: the state space approach" by Hyndman, Koehler, Ord and Snyder (Springer, 2008).

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7.40 score 15 stars 2 dependents 135 scripts 4.1k downloads

Mcomp - Data from the M-Competitions

The 1001 time series from the M-competition (Makridakis et al. 1982) <DOI:10.1002/for.3980010202> and the 3003 time series from the IJF-M3 competition (Makridakis and Hibon, 2000) <DOI:10.1016/S0169-2070(00)00057-1>.

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forecastingtime-series

7.35 score 12 stars 2 dependents 326 scripts 2.4k downloads

thief - Temporal Hierarchical Forecasting

Methods and tools for generating forecasts at different temporal frequencies using a hierarchical time series approach.

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6.81 score 48 stars 2 dependents 88 scripts 2.6k downloads