IKPLS
IKPLS: A free, open-source Python package focused on iterative and kernel PLS regression. Ranked #73 of 106 in Statistical Analysis Software by our editors (3.0/10); pricing: Free plan; best for python users applying partial least-squares methods.
At a glance
- Editor score3.0 / 10
- PricingFree plan
- Best forPython users applying partial least-squares methods
- Free planYes
- Paid fromFree
- DeploymentDesktop
- Facts checked23 Sep 2026
Where it wins
- Iterative and kernel-based PLS algorithms for multivariate regression
- Free, open-source package for local Python workflows
- Runs on Linux, macOS, and Windows environments
Where it doesn't
- Focuses narrowly on partial least-squares methods
- Requires self-hosted execution in a Python environment
- Support is provided through documentation channels
Our verdict on IKPLS
IKPLS is a Python package for statistical workflows involving multivariate data and partial least-squares regression. It provides iterative partial least-squares algorithms and kernel-based partial least-squares modeling through a programmable interface. The package is aimed at solo analysts and small to mid-market teams that already work in Python and need PLS methods executed locally rather than through a hosted application. Its desktop-style, self-hosted deployment supports Linux, macOS, and Windows environments.
The published model is free and open source, so users can run IKPLS without a paid plan structure. Execution takes place in the user’s own Python environment, which keeps processing local and fits scripting-based workflows. Documentation is available through Read the Docs, giving users a reference point for implementation and configuration. Teams planning production use should review the project repository for licensing terms, documentation coverage, and supported input formats before standardizing on the package.
IKPLS’s main strength is depth within a specific method family: iterative and kernel-based PLS algorithms for multivariate regression. That focus can suit researchers or analysts whose work centers on PLS and who value a Python programming interface. It is less appropriate for organizations seeking a broad statistical analysis suite, managed hosting, or a graphical workflow outside Python. Buyers should choose IKPLS when local, scriptable PLS modeling is the priority; teams needing wider modeling coverage or a hosted platform should look elsewhere.
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IKPLS pricing
IKPLS fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment | Desktop |
| Statistical tests | Not verified |
| Regression models | Yes |
| Scripting support | Yes |
| Bayesian analysis | Not verified |
| Data import formats | Not verified |
| Deployment | Self-hosted |
| Platforms | Linux, macOS, Windows |
| Support | Docs |
| Built for | Solo, Small business, Mid-market (editorial estimate) |
| Pricing | Free plan |
| Website | ikpls.readthedocs.io |
| Facts checked | 23 Sep 2026 |
Alternatives to IKPLS
- RA free, programmable environment for statistical analysis, modeling, visualization, and data import.9.4
- StataA broad, scriptable desktop environment for professional and reproducible applied analysis.9.3
- IBM SPSS StatisticsA broad desktop statistics suite with testing, modeling, forecasting, reporting, and R/Python integration.9.2
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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