https://github.com/viraltux/forecast.jl
Julia package containing utilities intended for Time Series analysis.
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.3%) to scientific vocabulary
Keywords
Repository
Julia package containing utilities intended for Time Series analysis.
Basic Info
Statistics
- Stars: 48
- Watchers: 2
- Forks: 8
- Open Issues: 9
- Releases: 0
Topics
Metadata Files
README.md
Forecast 
Julia package containing utilities intended for Time Series analysis.
:warning: This package is in an early development stage and its functionality has not been thoroughly tested. Please, consider to report issues if you find any.
:warning: This package is undergoing heavy refactoring and is in a feature freeze status.
Featured Methods
- Autocorrelated models for univariate and multivariate data (ar)
- Autocorrelated model simulations for univariate and multivariate data (arsim)
- Autocorrelated model forecasting with custom plots (forecast)
- Autocorrelation & Autocovariance function and custom plots (acf)
- Boxcox Transformations and Inverse Boxcox Transformations (boxcox, iboxcox)
- Crosscorrelation & Crosscovariance function and custom plots (ccf)
- Henderson Moving Average Filter (hma)
- Lagged differences and Reverse lagged differences of a given order (d | p)
- Locally Estimated Scatterplot Smoothing (loess)
- Seasonal and Trend decomposition based on Loess and custom plot (stl)
- Seasonal Plot for series and Time Series (splot)
- Simple Moving Average (sma)
Datasets
- Atmospheric Carbon Dioxide Dry Air Mole Fractions from quasi-continuous measurements at Mauna Loa, Hawaii.
K.W. Thoning, A.M. Crotwell, and J.W. Mund (2020), Atmospheric Carbon Dioxide Dry Air Mole Fractions from continuous measurements at Mauna Loa, Hawaii, Barrow, Alaska, American Samoa and South Pole. 1973-2019, Version 2020-08 National Oceanic and Atmospheric Administration (NOAA), Global Monitoring Laboratory (GML), Boulder, Colorado, USA DOI
FTP path: ftp://aftp.cmdl.noaa.gov/data/greenhouse_gases/co2/in-situ/surface/
- Airline Passengers
The classic Box & Jenkins airline data. Monthly totals of international airline passengers from 1949 to 1960. Box, G. E. P., Jenkins, G. M. and Reinsel, G. C. (1976) Time Series Analysis, Forecasting and Control. Third Edition. Holden-Day. Series G.
- London Crime and Weather
Ten years of monthly data about weather and crime in Greater London from 2008 to 2018. Data has been collected and joined from London Assembly and Met Office (Heathrow Station).
- Estimates of world seaborne trade from AIS data collected by MarineTraffic; available at UN COMTRADE Monitor.
Cerdeiro, Komaromi, Liu and Saeed (2020). Subset with imports and exports data for France, Germany and the United Kingdom from 2015-04-01 to 2021-05-02. UN Comtrade Database
- Large Earthquakes
Number of earthquakes per year on earth with a magnitude higher or equal to six from 1950 to 2020.The data has been collected from the U.S. Geological Survey and aggregated.
References
- [Cleveland et al. 1990] Cleveland, R. B.; Cleveland, W. S.;McRae, J. E.; and Terpenning, I. 1990. STL: A seasonal-trend decomposition procedure based on loess. Journal of Official Statistics 6(1):3–73.
- Henderson, R. (1916). Note on graduation by adjusted average. Transactions of the Actuarial Society of America, 17:43-48. Australian Bureau of Statistics: What Are Henderson Moving Averages?
Owner
- Name: Fran Urbano
- Login: viraltux
- Kind: user
- Website: aleadeum.com
- Repositories: 7
- Profile: https://github.com/viraltux
Faster than Stephen Hawkins and smarter than Usain Bolt.
GitHub Events
Total
- Watch event: 3
Last Year
- Watch event: 3
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 263
- Total Committers: 4
- Avg Commits per committer: 65.75
- Development Distribution Score (DDS): 0.11
Top Committers
| Name | Commits | |
|---|---|---|
| Fran Urbano | v****x@g****m | 234 |
| github-actions[bot] | 4****]@u****m | 25 |
| val@plstr.com | v****l@p****m | 2 |
| Pietro Monticone | 3****e@u****m | 2 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 8
- Total pull requests: 68
- Average time to close issues: about 1 month
- Average time to close pull requests: about 1 month
- Total issue authors: 7
- Total pull request authors: 7
- Average comments per issue: 2.0
- Average comments per pull request: 0.72
- Merged pull requests: 42
- Bot issues: 0
- Bot pull requests: 41
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- vly (2)
- Natalieburke1 (1)
- eliascarv (1)
- timesselens (1)
- guilhermebodin (1)
- JuliaTagBot (1)
- josemanuel22 (1)
Pull Request Authors
- github-actions[bot] (41)
- viraltux (19)
- pitmonticone (3)
- vly (2)
- gustafsson (1)
- ayushpatnaikgit (1)
- quinnj (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- julia 4 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 1
juliahub.com: Forecast
Julia package containing utilities intended for Time Series analysis.
- Documentation: https://docs.juliahub.com/General/Forecast/stable/
- License: MIT
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Latest release: 0.1.0
published over 4 years ago