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[regression] some more notes

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Jan Benda 2019-12-12 08:49:27 +01:00
parent a7e64a5c6d
commit f2778e2fe2
3 changed files with 15 additions and 7 deletions
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4
bootstrap/lecture/bootstrap-chapter.tex
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@ -17,10 +17,10 @@
\include{bootstrap} \include{bootstrap}
\section{TODO} \section{TODO}
This chapter easily covers two lectures:
\begin{itemize} \begin{itemize}
\item This chapter easily covers two lectures:
\item 1. Bootstrapping with a proper introduction of of confidence intervals \item 1. Bootstrapping with a proper introduction of of confidence intervals
\item 2. Permutation test with a proper introduction of statistical tests (dsitrubution of nullhypothesis significance, power, etc.) \item 2. Permutation test with a proper introduction of statistical tests (dsitribution of nullhypothesis, significance, power, etc.)
\end{itemize} \end{itemize}
\end{document} \end{document}

14
regression/lecture/regression-chapter.tex
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@ -23,15 +23,21 @@
\subsection{Start with one-dimensional problem!} \subsection{Start with one-dimensional problem!}
\begin{itemize} \begin{itemize}
\item Just the root mean square as a function of the slope \item Let's fit a cubic function $y=cx^3$ (weight versus length of a tiger)
\item 1-d gradient \item Introduce the problem, $c$ is density and form factor
\item How to generate an artificial data set (refer to simulation chapter)
\item How to plot a function (do not use the data x values!)
\item Just the mean square error as a function of the factor c
\item Also mention the cost function for a straight line
\item 1-d gradient, NO quiver plot (it is a nightmare to get this right)
\item 1-d gradient descend \item 1-d gradient descend
\item Homework is to do the 2d problem! \item Describe in words the n-d problem.
\item Homework is to do the 2d problem with the straight line!
\end{itemize} \end{itemize}
\subsection{Linear fits} \subsection{Linear fits}
\begin{itemize} \begin{itemize}
\item Polyfit is easy: unique solution! \item Polyfit is easy: unique solution! $c x^2$ is also a linear fit.
\item Example for overfitting with polyfit of a high order (=number of data points) \item Example for overfitting with polyfit of a high order (=number of data points)
\end{itemize} \end{itemize}

4
scientificcomputing-script.tex
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@ -58,7 +58,9 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\part{Data analysis} \part{Data analysis}
% add chapter on simulations (euler forward, odeint) % add chapter on simulations (draw random numbers, draw random functions, euler forward, odeint)
% this would be a nice and simple starter!
% introduces derivatives which are also needed for fitting
\includechapter{statistics} \includechapter{statistics}