future VS hts

Compare future vs hts and see what are their differences.

hts

Hierarchical and Grouped Time Series (by earowang)
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
future hts
2 3
932 107
- -
8.1 0.0
14 days ago over 1 year ago
R R
- -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

future

Posts with mentions or reviews of future. We have used some of these posts to build our list of alternatives and similar projects.

hts

Posts with mentions or reviews of hts. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-07-19.
  • Time Series Forecasting Compositional Data - no good package exists?
    1 project | /r/rstats | 25 Dec 2022
  • [P] Fastest and most accurate version of the Exponential Smoothing (ETS) Algorithm for Python
    3 projects | /r/MachineLearning | 19 Jul 2022
    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)
  • Can anyone explain me hierarchical time series forecating?
    1 project | /r/datascience | 16 Nov 2021
    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?

When comparing future and hts you can also consider the following projects:

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.