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.

Last updated 5 months ago

forecastforecastingopenblascpp

18.59 score 1.1k stars 234 dependents 16k scripts 166k 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.

Last updated 7 months ago

14.47 score 535 stars 40 dependents 4.4k scripts 23k 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.

Last updated 2 months ago

forecastingcpp

13.52 score 564 stars 6 dependents 2.0k scripts 15k 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.

Last updated 18 days ago

probability-distributionstatisticsvctrs

13.41 score 101 stars 372 dependents 744 scripts 61k 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.

Last updated 2 months ago

12.58 score 297 stars 7 dependents 1.3k scripts 17k 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.

Last updated 3 months ago

12.19 score 89 stars 17 dependents 396 scripts 19k downloads

rticles - Article Formats for R Markdown

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

Last updated 15 days ago

articlejournalpaperrmarkdown

11.50 score 1.5k stars 2 dependents 188 scripts 4.0k 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.

Last updated 6 months ago

feature-extractiontime-series

11.41 score 254 stars 22 dependents 270 scripts 11k downloads

vitae - Curriculum Vitae for R Markdown

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

Last updated 7 months ago

cvozunconf18resumeunconf

10.72 score 1.2k stars 556 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.

Last updated 2 years ago

fortran

10.25 score 23 stars 158 dependents 131 scripts 10k 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>.

Last updated 28 days ago

forecastshtscpp

9.67 score 110 stars 5 dependents 214 scripts 4.4k 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/>.

Last updated 1 years ago

8.47 score 19 stars 2 dependents 320 scripts 5.4k 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.

Last updated 2 years ago

dataforecasting

8.32 score 105 stars 1 dependents 1.8k scripts 7.1k 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'.

Last updated 1 months ago

beamerbeamer-presentationbeamer-thememarkdownpdfrmarkdownrmarkdown-beamer

8.31 score 189 stars 2 dependents 2 scripts 359 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.

Last updated 2 months ago

datasettsibble

8.30 score 25 stars 2 dependents 692 scripts 7.7k 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.

Last updated 4 months ago

dataforecasting

8.23 score 139 stars 2.4k scripts 8.5k 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.

Last updated 2 months ago

actuarialdemographyforecasting

8.12 score 74 stars 6 dependents 241 scripts 2.1k 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).

Last updated 3 months ago

cpp

7.90 score 41 stars 1 dependents 206 scripts 1.3k 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.

Last updated 1 years ago

cricketcricket-dataozunconf17unconf

7.81 score 85 stars 85 scripts 370 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.

Last updated 11 months ago

statistical-graphicstime-series

7.42 score 82 stars 1 dependents 214 scripts 438 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).

Last updated 2 years ago

7.34 score 14 stars 2 dependents 105 scripts 5.0k 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>.

Last updated 7 months ago

forecastingtime-series

7.04 score 12 stars 2 dependents 274 scripts 1.4k 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.

Last updated 2 days ago

7.01 score 7 stars 2 dependents 1.2k scripts 720 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>.

Last updated 10 months ago

data-generationmixture-autoregressivestatistical-computingtime-series

6.98 score 76 stars 25 scripts 236 downloads

thief - Temporal Hierarchical Forecasting

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

Last updated 2 years ago

6.73 score 48 stars 2 dependents 79 scripts 2.3k 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.

Last updated 2 years ago

australiaauunconfcensus-dataelectionunconf

6.66 score 43 stars 193 scripts 79 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.

Last updated 1 months ago

6.11 score 28 stars 17 scripts 116 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 (2024) "That's Weird: Anomaly Detection Using R" <https://OTexts.com/weird/>. All packages needed to run the examples are also loaded.

Last updated 1 months ago

5.75 score 15 stars 18 scripts 190 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.

Last updated 5 years ago

5.62 score 105 stars 80 scripts

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.

Last updated 1 years ago

stray

5.47 score 58 stars 1 dependents 34 scripts 304 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>.

Last updated 2 years ago

5.31 score 79 stars 52 scripts 187 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.

Last updated 3 months ago

ozunconf18unconf

5.19 score 10 stars 26 scripts 423 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.

Last updated 4 months ago

5.00 score 22 stars 4 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.

Last updated 9 months ago

4.95 score 30 stars 2 dependents 9 scripts 245 downloads

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

Implementation of the FASSTER model for forecasting time series with multiple seasonalities using switching states.

Last updated 2 years ago

4.90 score 149 stars 106 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.

Last updated 3 years ago

4.74 score 52 stars 35 scripts 24 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>.

Last updated 5 years ago

4.71 score 64 stars 16 scripts 153 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.

Last updated 2 years ago

datatime-series

4.69 score 18 stars 18 scripts

rcademy - Tools to assist with academic promotions

Ideas and tools to help with preparing documentation for promotions at universities.

Last updated 4 months ago

4.23 score 14 stars 9 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>.

Last updated 8 months ago

4.22 score 3 stars 11 scripts 134 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.

Last updated 7 months ago

3.92 score 55 stars 1 dependents 7 scripts 511 downloads

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

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

Last updated 11 months ago

3.00 score 2 stars 6 scripts

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.

Last updated 5 years ago

2.74 score 11 stars 7 scripts

conduits - CONDitional UI for Time Series normalisation

Provide a user interface for conditionally normalising a timeseries.

Last updated 2 years ago

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.

Last updated 1 years ago

2.54 score 7 stars 4 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.

Last updated 2 years ago

2.30 score 4 stars

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>.

Last updated 4 years ago

2.30 score 4 stars 140 downloads

TACforecasting - Forecasting Functions for the Transport Accident Commission

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

Last updated 2 years ago

2.00 score 2 stars 3 scripts

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.

Last updated 1 years ago

1.30 score 2 stars 3 scripts