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Compare asymptotic MISE behaviour for kernel and logspline density estimators as n → ∞ in a Monte Carlo experiment.

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tobikuhlmann/non-parametric-density-estimation

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Non-parametric-Density-Estimation

UMass Amherst STAT 797 (Non parametric regression methods) class project together with Rui Zhang.

Our research aim is to compare asymptotic MISE behaviour for kernel and logspline density estimators as n → ∞ in a Monte Carlo experiment.

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Compare asymptotic MISE behaviour for kernel and logspline density estimators as n → ∞ in a Monte Carlo experiment.

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