forecast
HoRM
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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
HoRM
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James Bond Film Dataset
- https://github.com/dsy109/HoRM
What are some alternatives?
parsel - parallel execution of RSelenium
polished_example_apps - Example Apps for Polished
lmForc - R package for evaluating linear forecasting models.
mindr - an R package which converts markdown files (.md, .Rmd) into mindmaps (brainstorms)
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
easystats - :milky_way: The R easystats-project
rtypeform - An R interface to the 'typeform' API.
ggstatsplot - Enhancing {ggplot2} plots with statistical analysis 📊📣
tsfel - An intuitive library to extract features from time series.
electricShine - Create Standalone Installable Shiny Apps