tridiag

Generate a tridiagonal matrix with <code>upperDiag</code> as superdiagonal, 
<code>lowerDiag</code> as subdiagonal and <code>mainDiag</code> as diagonal.

A method for the multiresolution analysis of spatial fields and images to capture scale-dependent features.
mrbsizeR is based on scale space smoothing and uses differences of smooths at neighbouring scales for finding features on different scales.
To infer which of the captured features are credible, Bayesian analysis is used.
The scale space multiresolution analysis has three steps: (1) Bayesian signal reconstruction.
(2) Using differences of smooths, scale-dependent features of the reconstructed signal can be found.
(3) Posterior credibility analysis of the differences of smooths created.
The method has first been proposed by Holmstrom, Pasanen, Furrer, Sain (2011) <DOI:10.1016/j.csda.2011.04.011> and extended in Flury, Gerber, Schmid and Furrer (2021) <DOI:10.1016/j.spasta.2020.100483>.

Roman Flury

mrbsizeR

Scale Space Multiresolution Analysis of Random Signals

Thimo Schuster

Leena Pasanen

Reinhard Furrer

tridiag function

<dl><dt>mainDiag</dt>
<dd>Diagonal of tridiagonal matrix.</dd>
<dt>upperDiag</dt>
<dd>Superdiagonal of tridiagonal matrix. Must have length <code>length(mainDiag) - 1</code>.</dd>
<dt>lowerDiag</dt>
<dd>Subdiagonal of tridiagonal matrix. Must have length <code>length(mainDiag) - 1</code>.</dd></dl>

Arguments

Generate a tridiagonal matrix. — tridiag

<dl>

<dt>mainDiag</dt>
<dd>Diagonal of tridiagonal matrix.</dd>


<dt>upperDiag</dt>
<dd>Superdiagonal of tridiagonal matrix. Must have length <code>length(mainDiag) - 1</code>.</dd>


<dt>lowerDiag</dt>
<dd>Subdiagonal of tridiagonal matrix. Must have length <code>length(mainDiag) - 1</code>.</dd>

</dl>

tridiag: Generate a tridiagonal matrix.

Description

Usage

Value

Arguments

Examples