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small lit fix

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toni
2018-02-24 13:58:41 +01:00
parent 1b6445fa65
commit 8523e7040d
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tex/chapters/relatedwork.tex
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@@ -42,7 +42,7 @@ In general, it is desirable to omit a grid, as the data points do not necessary
However, reducing the sample size by distributing the data on a equidistant grid can significantly reduce the computation time, if an approximative KDE is acceptable.
Silverman \cite{silverman1982algorithm} originally suggested to combine adjacent data points into data bins, which results in a discrete convolution structure of the KDE.
Allowing to efficiently compute the estimate using a FFT algorithm.
This approximation scheme was later called binned KDE (BKDE) and was extensively studied \cite{fan1994fast} \cite{wand1994fast} \cite{hall1996accuracy} \cite{holmstrom2000accuracy}.
This approximation scheme was later called binned KDE (BKDE) and was extensively studied \cite{fan1994fast} \cite{wand1994fast} \cite{hall1996accuracy}.
While the FFT algorithm poses an efficient algorithm for large sample sets, it adds an noticeable overhead for smaller ones.
The idea to approximate a Gaussian filter using several box filters was first formulated by Wells \cite{wells1986efficient}.