bayes

Given a linear inverse problem Gm=d, a prior mean mprior and covariance
 matrix covm, data d, and data covariance matrix covd, this function
 computes the MAP solution and the corresponding covariance matrix.

misc

Several functions introduced in Aster et al.'s book on inverse theory. The functions are often translations of MATLAB code developed by the authors to illustrate concepts of inverse theory as applied to geophysics. Generalized inversion, tomographic inversion algorithms (conjugate gradients, 'ART' and 'SIRT'), non-linear least squares, first and second order Tikhonov regularization, roughness constraints, and procedures for estimating smoothing parameters are included.

Jonathan Lees

PEIP

Geophysical Inverse Theory and Optimization

Jonathan M. Lees

bayes function

<dl> <dt>G</dt>
<dd>Design Matrix</dd> <dt>mprior</dt>
<dd>vector, prior model</dd> <dt>covm</dt>
<dd>vector, model covariance</dd> <dt>d</dt>
<dd>vector, right hand side</dd> <dt>covd</dt>
<dd>vector, data covariance</dd></dl>

Arguments

Jonathan M. Lees&lt;jonathan.lees@unc.edu&gt;

Author

Bayes Inversion — bayes

<dl>

 <dt>G</dt>
<dd>Design Matrix</dd>

 <dt>mprior</dt>
<dd>vector, prior model</dd>

 <dt>covm</dt>
<dd>vector, model covariance</dd>

 <dt>d</dt>
<dd>vector, right hand side</dd>

 <dt>covd</dt>
<dd>vector, data covariance</dd>

</dl>

bayes: Bayes Inversion

Description

Usage

Value

Arguments

Author

References