added first draf real world experiments
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@@ -26,7 +26,7 @@ The MISE between $f$ and the estimates as a function of $h$ are evaluated, and t
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\begin{figure} [t]
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\label{fig:evalBandwidth}
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\includegraphics[width=\columnwidth]{gfx/Eval1Bandwidth_abs.png}
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\caption{Bla.} \label{fig:eval1GroundTruth}
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\caption{Hier kommt Performance Plot 2 spaltig} \label{fig:eval1GroundTruth}
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\end{figure}
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Other test cases of theoretical relevance are error as a function of the grid size $G$ and the sample size $N$.
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@@ -42,4 +42,17 @@ All tests are performed on a Intel Core \mbox{i5-7600K} CPU with a frequency of
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We compare our C++ implementation of the box filter based KDE to the KernSmooth R package and the \qq{FastKDE} implementation \cite{oBrien2016fast}.
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The KernSmooth packages provides a FFT-based BKDE implementation based on optimized C functions at its core.
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\begin{figure} [t]
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\label{fig:evalBandwidth}
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\includegraphics[width=\columnwidth]{gfx/Eval1Bandwidth_abs.png}
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\caption{Hier kommt Performance Plot 2 spaltig} \label{fig:eval1GroundTruth}
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\end{figure}
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\begin{figure} [b]
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\label{fig:evalBandwidth}
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\includegraphics[width=\columnwidth]{gfx/Eval1Bandwidth_abs.png}
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\caption{Hier kommt bandwith error plot single} \label{fig:eval1GroundTruth}
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\end{figure}
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\input{chapters/realworld}
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