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

20.53 score 1.2k stars 1.3k dependents 22k scripts 484k 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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14.96 score 544 stars 43 dependents 6.2k scripts 26k 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

14.50 score 113 stars 440 dependents 1.2k scripts 391k 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

13.43 score 583 stars 7 dependents 2.4k scripts 12k 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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12.51 score 309 stars 9 dependents 1.9k scripts 10k 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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12.45 score 96 stars 24 dependents 590 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

11.80 score 1.5k stars 3 dependents 179 scripts 11k 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-series

11.68 score 261 stars 21 dependents 358 scripts 18k 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

11.20 score 1.3k stars 776 scripts 1.0k 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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11.02 score 25 stars 173 dependents 158 scripts 14k 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

9.17 score 157 stars 3.2k scripts 7.4k 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

9.08 score 77 stars 7 dependents 282 scripts 5.3k 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

9.07 score 108 stars 1 dependents 2.4k scripts 10.0k 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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8.73 score 24 stars 10 dependents 81 scripts 10k 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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8.57 score 19 stars 2 dependents 357 scripts 6.0k 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

8.44 score 113 stars 5 dependents 203 scripts 3.2k 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

8.30 score 27 stars 2 dependents 796 scripts 6.2k 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

8.02 score 53 stars 1 dependents 217 scripts 1.3k 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

8.01 score 191 stars 2 dependents 2 scripts 704 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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7.96 score 9 stars 1 dependents 1.7k scripts 701 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

7.90 score 91 stars 97 scripts 357 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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7.78 score 32 stars 26 scripts 165 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

7.74 score 12 stars 2 dependents 408 scripts 4.7k 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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7.60 score 15 stars 2 dependents 155 scripts 5.7k 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

7.53 score 81 stars 1 dependents 277 scripts 418 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

7.40 score 78 stars 43 scripts 312 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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7.22 score 43 stars 1 dependents 52 scripts 566 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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6.83 score 48 stars 2 dependents 90 scripts 2.6k downloads

eechidna - Exploring Election and Census Highly Informative Data Nationally for Australia

Data from the seven Australian Federal Elections (House of Representatives) between 2001 and 2019, and from the four Australian Censuses over the same period. Includes tools for visualizing and analysing the data, as well as imputing Census data for years in which a Census does not occur. This package incorporates data that is copyright Commonwealth of Australia (Australian Electoral Commission and Australian Bureau of Statistics) 2019.

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australiaauunconfcensus-dataelectionunconf

6.63 score 44 stars 175 scripts 44 downloads

fasster - Fast Additive Switching of Seasonality, Trend, and Exogenous Regressors

Implementation of the FASSTER (Forecasting with Additive Switching of Seasonality, Trend, and Exogenous Regressors) model for forecasting time series with multiple seasonal patterns. The model combines state space methodology with a switching component in the observation equation to allow flexible modeling of complex seasonal patterns, including time-varying effects and multiple seasonalities.

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6.42 score 153 stars 114 scripts 149 downloads

calcal - Calendrical Calculations

An R implementation of the algorithms described in Reingold and Dershowitz (4th ed., Cambridge University Press, 2018) <doi:10.1017/9781107415058>, allowing conversion between many different calendar systems. Cultural and religious holidays from several calendars can be calculated.

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6.26 score 13 stars 4 scripts 188 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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6.02 score 22 stars 32 scripts 349 downloads

tsdl - Time Series Data Library

The Time Series Data Library (TSDL) https://datamarket.com/data/list/?q=provider:tsdl was created by Rob Hyndman, Professor of Statistics at Monash University, Australia.

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5.74 score 115 stars 96 scripts

lookout - Leave One Out Kernel Density Estimates for Outlier Detection

Outlier detection using leave-one-out kernel density estimates and extreme value theory. The bandwidth for kernel density estimates is computed using persistent homology, a technique in topological data analysis. Using peak-over-threshold method, a generalized Pareto distribution is fitted to the log of leave-one-out kde values to identify outliers.

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5.48 score 29 stars 1 dependents 10 scripts 570 downloads

stray - Anomaly Detection in High Dimensional and Temporal Data

This is a modification of 'HDoutliers' package. The 'HDoutliers' algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. This package implements the algorithm proposed in Talagala, Hyndman and Smith-Miles (2019) <arXiv:1908.04000> for detecting anomalies in high-dimensional data that addresses these limitations of 'HDoutliers' algorithm. We define an anomaly as an observation that deviates markedly from the majority with a large distance gap. An approach based on extreme value theory is used for the anomalous threshold calculation.

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stray

5.48 score 59 stars 1 dependents 34 scripts 250 downloads

seer - Feature-Based Forecast Model Selection

A novel meta-learning framework for forecast model selection using time series features. Many applications require a large number of time series to be forecast. Providing better forecasts for these time series is important in decision and policy making. We propose a classification framework which selects forecast models based on features calculated from the time series. We call this framework FFORMS (Feature-based FORecast Model Selection). FFORMS builds a mapping that relates the features of time series to the best forecast model using a random forest. 'seer' package is the implementation of the FFORMS algorithm. For more details see our paper at <https://www.monash.edu/business/econometrics-and-business-statistics/research/publications/ebs/wp06-2018.pdf>.

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5.32 score 78 stars 54 scripts 286 downloads

ozbabynames - Australian Popular Baby Names

Data on the most popular baby names by sex and year, and for each state in Australia, as provided by the state and territory governments. The quality and quantity of the data varies with the state.

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ozunconf18unconf

5.24 score 12 stars 24 scripts 131 downloads

monash - Consolidated tools and templates for staff at Monash University

Rmarkdown templates and other tools for use at Monash University, Department of Econometrics & Business Statistics.

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5.16 score 24 stars 6 scripts

gghdr - Visualisation of Highest Density Regions in 'ggplot2'

Provides 'ggplot2' framework for visualising Highest Density Regions (HDR) <doi:10.1080/00031305.1996.10474359>. This work is based on the package 'hdrcde'<https://pkg.robjhyndman.com/hdrcde/> and displays highest density regions in 'ggplot2' for one and two dimensions and univariate densities conditional on one covariate.

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4.81 score 54 stars 40 scripts 11 downloads

oddstream - Outlier Detection in Data Streams

We proposes a framework that provides real time support for early detection of anomalous series within a large collection of streaming time series data. By definition, anomalies are rare in comparison to a system's typical behaviour. We define an anomaly as an observation that is very unlikely given the forecast distribution. The algorithm first forecasts a boundary for the system's typical behaviour using a representative sample of the typical behaviour of the system. An approach based on extreme value theory is used for this boundary prediction process. Then a sliding window is used to test for anomalous series within the newly arrived collection of series. Feature based representation of time series is used as the input to the model. To cope with concept drift, the forecast boundary for the system's typical behaviour is updated periodically. More details regarding the algorithm can be found in Talagala, P. D., Hyndman, R. J., Smith-Miles, K., et al. (2019) <doi:10.1080/10618600.2019.1617160>.

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4.74 score 64 stars 17 scripts 194 downloads

tscompdata - Time series data from various forecasting competitions

Time series data from the following forecasting competitions are provided: M, M3, NN3, NN5, NNGC1, Tourism, and GEFCom2012.

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datatime-series

4.69 score 18 stars 18 scripts

spiderorchid - Download and wrangle publication data for Monash EBS academic staff

Provide journal rankings from Monash Business School, ABDC, CORE, Scimago and ERA 2010. Fetch publication details from ORCID, Google Scholar, PURE and from DOIs. Find CRAN packages and download statistics for specified authors.

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4.32 score 1 stars 7 scripts

oddnet - Anomaly Detection in Temporal Networks

Anomaly detection in dynamic, temporal networks. The package 'oddnet' uses a feature-based method to identify anomalies. First, it computes many features for each network. Then it models the features using time series methods. Using time series residuals it detects anomalies. This way, the temporal dependencies are accounted for when identifying anomalies (Kandanaarachchi, Hyndman 2022) <arXiv:2210.07407>.

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4.22 score 3 stars 11 scripts 177 downloads

MEFM - Monash Electricity Forecasting Model

This package includes a set of tools for implementing the Monash Electricity Forecasting Model for electricity demand. The package requires the following data as input: half-hourly/hourly electricity demands; half-hourly/hourly temperatures at one or two locations; seasonal demographical and economical data; public holiday data. The formats of the required data are described in the help files.

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3.92 score 55 stars 1 dependents 8 scripts 609 downloads

oddwater - Outlier Detection in Data from Water-Quality Sensors

We propose a framework to detect technical outliers in water quality data from in situ sensors.

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2.74 score 11 stars 7 scripts

conduits - CONDitional UI for Time Series normalisation

Provide a user interface for conditionally normalising a timeseries.

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2.73 score 3 stars 18 scripts

fable.binary - Forecasting Binary Time Series

Provides a collection of time series forecasting models suitable for binary time series. 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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2.60 score 8 stars 4 scripts

Rsfar - Seasonal Functional Autoregressive Models

This is a collection of functions designed for simulating, estimating and forecasting seasonal functional autoregressive time series of order one. These methods are addressed in the manuscript: <https://www.monash.edu/business/ebs/research/publications/ebs/wp16-2019.pdf>.

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2.40 score 5 stars 243 downloads

pkgmeta - Find details about R packages on CRAN or github

Finds meta data for all packages on CRAN that match a given author and packages contained in specified github repositories.

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2.30 score 4 stars 10 scripts

addb - Australian Demographic Data Bank

These data are from the Australian Demographic Data Bank. They can be plotted and analysed using the demography package.

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2.30 score 4 stars

compenginets - Time series from <https://www.comp-engine.org/>

All time series from the comp-engine database are included, along with some meta data.

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2.00 score 2 stars 9 scripts

TACforecasting - Forecasting Functions for the Transport Accident Commission

Functions to make hierarchical time series forecasts of attendant care hours easier.

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2.00 score 2 stars 3 scripts