lmForc
forecast
| lmForc | forecast | |
|---|---|---|
| 5 | 2 | |
| 5 | 1,098 | |
| - | - | |
| 2.9 | 7.1 | |
| about 2 months ago | 15 days ago | |
| R | R | |
| GNU General Public License v3.0 only | - |
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lmForc
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[S] R Package for Creating Linear Forecasting Models
GitHub: https://github.com/nelson-n/lmForc
- [S] New R package for linear model forecasting
- New R package for linear model forecasting
forecast
- Repost - R Package for Creating Linear Forecasting Models
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Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
As a few other people have mentioned, I find R to be the easiest tool for this job, specifically the forecast package [0]. I had to use this package for an applied econometrics course in college a few years ago, and I have been using it ever since. I find the syntax to be more straightforward than comparable libraries in Python. I also assume that this library (and other libraries in R) offer higher quality models and results than their counterparts in Python, but this is just an assumption.
[0] https://github.com/robjhyndman/forecast
What are some alternatives?
bruceR - 📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.
parsel - parallel execution of RSelenium
nflfastR - A Set of Functions to Efficiently Scrape NFL Play by Play Data
Peptides - An R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.
future - :rocket: R package: future: Unified Parallel and Distributed Processing in R for Everyone
modeltime.ensemble - Time Series Ensemble Forecasting
huxtable - An R package to create styled tables in multiple output formats, with a friendly, modern interface.
rtypeform - An R interface to the 'typeform' API.
HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"
tsfel - An intuitive library to extract features from time series.
darts - A python library for user-friendly forecasting and anomaly detection on time series.