modeltime.ensemble
forecast
modeltime.ensemble | forecast | |
---|---|---|
1 | 2 | |
71 | 1,100 | |
- | - | |
7.6 | 7.1 | |
5 months ago | about 1 month ago | |
R | R | |
GNU General Public License v3.0 or later | - |
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modeltime.ensemble
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?
fable - Tidy time series forecasting
parsel - parallel execution of RSelenium
modeltime.resample - Resampling Tools for Time Series Forecasting with Modeltime
lmForc - R package for evaluating linear forecasting models.
boostime - The Tidymodels Extension for Time Series Boosting Models
Peptides - An R package to calculate indices and theoretical physicochemical properties of peptides and protein sequences.
timetk - Time series analysis in the `tidyverse`
rtypeform - An R interface to the 'typeform' API.
modeltime - Modeltime unlocks time series forecast models and machine learning in one framework
HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"
Econometrics-on-Stock-Data - R finance guide - Algotrading101
tsfel - An intuitive library to extract features from time series.