future
hts
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future
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Running Code in Parallel
Check out the future package: https://github.com/HenrikBengtsson/future
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What's faster: run simultaneously on multiple terminals, or run everything sequentially on one terminal?
If you're a fan of the tidyverse check out the furrr package, which is based on the future package. Let's you apply your map() functions in parallel very easily.
hts
- Time Series Forecasting Compositional Data - no good package exists?
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[P] Fastest and most accurate version of the Exponential Smoothing (ETS) Algorithm for Python
sadly a lot of statistics research is done with R and is unavailable with Python, hopefully this kind of work will also motivate new libraries for Python. I am particularly interested in hierarchical forecasting. Are there Python alternatives to the hts library?(https://github.com/earowang/hts)
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Can anyone explain me hierarchical time series forecating?
Additionally, you could use one of the more complex methods from the aforementioned hts package. This will allow you to make forecasts on all levels of the hierarchy, and use the bootstrapped errors to make adjustments to all forecasts in the hierarchy using a constrained least-squares approach, in order to make all forecasts sum-consistent (make the aggregates of the forecasts equal the forecasts of the aggregates). This allows you to model cannibalisation effects between different products, for example. However for this to work, you'd need quite good models, as the bootstrapped errors are taken as the 'wiggle room' for the adjustments, which means that if you have a badly fitting model, the adjustments might be quite large and no longer make sense (eg. be negative for a sales forecast).
What are some alternatives?
seurat - R toolkit for single cell genomics
statsforecast - Lightning ⚡️ fast forecasting with statistical and econometric models.
R-sharp - R# language is a kind of R liked vectorized language implements on .NET environment for the bioinformatics data analysis
telegram.bot - Develop a Telegram Bot with R
HoRM - Supplemental Functions and Datasets for "Handbook of Regression Methods"
rtweet - 🐦 R client for interacting with Twitter's [stream and REST] APIs
r2u - CRAN as Ubuntu Binaries
tableone - R package to create "Table 1", description of baseline characteristics with or without propensity score weighting
openxlsx - openxlsx - a fast way to read and write complex xslx files
RobinHood - An R interface for the RobinHood.com no commision investing site
parsel - parallel execution of RSelenium
hierarchicalforecast - Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.