Kernel Density
Julia library for kernel density estimation.
Pricing
Free tier
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Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Kernel Density?
KernelDensity.jl is a JuliaStats package providing tools for non-parametric kernel density estimation. It is useful in statistical analysis and data visualization tasks where understanding the distribution of data points is crucial.
Key differentiator
“KernelDensity.jl offers a robust set of tools for performing kernel density estimation in Julia, making it an ideal choice for researchers and developers who prioritize flexibility and precision over speed.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
KernelDensity.jl is specific to the Julia programming language, which may limit its accessibility for developers not familiar with or unable to use Julia.
As an open-source package within a niche ecosystem like JuliaStats, KernelDensity.jl might have less comprehensive documentation and fewer user-contributed examples compared to more widely-used libraries in larger ecosystems.
Kernel density estimation can be computationally intensive, especially for large datasets, potentially leading to slow performance or high memory usage.
Fit analysis
Who is it for?
✓ Best for
Researchers who need precise density estimation for small to medium-sized datasets
Julia developers working on statistical analysis projects that require flexible kernel functions
✕ Not a fit for
Projects requiring real-time density updates due to computational overhead
Large-scale data processing where performance is critical and non-parametric methods are not preferred
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
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Works well with
Next step
Get Started with Kernel Density
Step-by-step setup guide with code examples and common gotchas.