[Pkg-octave-commit] rev 780 - in
trunk/packages/octave2.9-forge/debian: . patches
Rafael Laboissiere
rafael at costa.debian.org
Sun Oct 22 15:22:39 UTC 2006
Author: rafael
Date: 2006-10-22 15:22:39 +0000 (Sun, 22 Oct 2006)
New Revision: 780
Added:
trunk/packages/octave2.9-forge/debian/patches/50-leasqr-doc.patch
Modified:
trunk/packages/octave2.9-forge/debian/changelog
trunk/packages/octave2.9-forge/debian/patches/
Log:
Added patch for improving leasqr documentation
Modified: trunk/packages/octave2.9-forge/debian/changelog
===================================================================
--- trunk/packages/octave2.9-forge/debian/changelog 2006-10-10 18:50:21 UTC (rev 779)
+++ trunk/packages/octave2.9-forge/debian/changelog 2006-10-22 15:22:39 UTC (rev 780)
@@ -1,5 +1,16 @@
-octave2.9-forge (2006.07.09+dfsg1-4) unstable; urgency=low
+octave2.9-forge (2006.07.09+dfsg1-5) unstable; urgency=low
+ NOT YET RELEASED!
+
+ [ Rafael Laboissiere ]
+ * debian/patches/50-leasqr-doc.patch: Improved documentation for leasqr.
+ Thanks to Francesco Potortì for the patch, which has also been applied
+ upstream (closes: #393495).
+
+ --
+
+Octave2.9-forge (2006.07.09+dfsg1-4) unstable; urgency=low
+
* Rebuilt for Octave 2.9.8 since the API number bumped from 21 to 22.
* debian/control: Build-depends on octave2.9 >= 2.9.9
Property changes on: trunk/packages/octave2.9-forge/debian/patches
___________________________________________________________________
Name: svn:ignore
+ *.log
Added: trunk/packages/octave2.9-forge/debian/patches/50-leasqr-doc.patch
===================================================================
--- trunk/packages/octave2.9-forge/debian/patches/50-leasqr-doc.patch (rev 0)
+++ trunk/packages/octave2.9-forge/debian/patches/50-leasqr-doc.patch 2006-10-22 15:22:39 UTC (rev 780)
@@ -0,0 +1,87 @@
+*** octave2.9-forge-2006.07.09+dfsg1.orig/main/optim/leasqr.m 2006-10-22 11:06:41.000000000 +0200
+--- octave2.9-forge-2006.07.09+dfsg1/main/main/optim/leasqr.m 2006-10-22 11:29:12.000000000 +0200
+@@ -22,24 +22,30 @@
+ % Levenberg-Marquardt nonlinear regression of f(x,p) to y(x).
+ %
+ % Version 3.beta
+-% {}= optional parameters
+-% x=vec or mat of indep variables, 1 row/observation: x=[x0 x1....xm]
+-% y=vec of obs values, same no. of rows as x.
+-% wt=vec(dim=length(x)) of statistical weights. These should be set
+-% to be proportional to (sqrt of var(y))^-1; (That is, the covariance
+-% matrix of the data is assumed to be proportional to diagonal with diagonal
+-% equal to (wt.^2)^-1. The constant of proportionality will be estimated.),
+-% default=ones(length(y),1).
+-% pin=vector of initial parameters to be adjusted by leasqr.
+-% dp=fractional incr of p for numerical partials,default= .001*ones(size(pin))
+-% dp(j)>0 means central differences.
+-% dp(j)<0 means one-sided differences.
+-% Note: dp(j)=0 holds p(j) fixed i.e. leasqr wont change initial guess: pin(j)
+-% F=name of function in quotes,of the form y=f(x,p)
+-% dFdp=name of partials M-file in quotes default is prt=dfdp(x,f,p,dp,F)
+-% stol=scalar tolerances on fractional improvement in ss,default stol=.0001
+-% niter=scalar max no. of iterations, default = 20
+-% options=matrix of n rows (same number of rows as pin) containing
++% Optional parameters are in braces {}.
++% x = column vector or matrix of independent variables, 1 row per
++% observation: x = [x0 x1....xm].
++% y = column vector of observed values, same number of rows as x.
++% wt = column vector (dim=length(x)) of statistical weights. These
++% should be set to be proportional to (sqrt of var(y))^-1; (That is,
++% the covariance matrix of the data is assumed to be proportional to
++% diagonal with diagonal equal to (wt.^2)^-1. The constant of
++% proportionality will be estimated.); default = ones(length(y),1).
++% pin = column vec of initial parameters to be adjusted by leasqr.
++% dp = fractional increment of p for numerical partial derivatives;
++% default = .001*ones(size(pin))
++% dp(j) > 0 means central differences on j-th parameter p(j).
++% dp(j) < 0 means one-sided differences on j-th parameter p(j).
++% dp(j) = 0 holds p(j) fixed i.e. leasqr wont change initial guess: pin(j)
++% F = name of function in quotes; the function shall be of the form y=f(x,p),
++% with y, x, p of the form y, x, pin as described above.
++% dFdp = name of partial derivative function in quotes; default is "dfdp", a
++% slow but general partial derivatives function; the function shall be
++% of the form prt=dfdp(x,f,p,dp,F) (see dfdp.m).
++% stol = scalar tolerance on fractional improvement in scalar sum of
++% squares = sum((wt.*(y-f))^2); default stol = .0001;
++% niter = scalar maximum number of iterations; default = 20;
++% options = matrix of n rows (same number of rows as pin) containing
+ % column 1: desired fractional precision in parameter estimates.
+ % Iterations are terminated if change in parameter vector (chg) on two
+ % consecutive iterations is less than their corresponding elements
+@@ -52,16 +58,16 @@
+ % default = Inf*ones().
+ %
+ % OUTPUT VARIABLES
+-% f=vec function values computed in function func.
+-% p=vec trial or final parameters. i.e, the solution.
+-% kvg=scalar: =1 if convergence, =0 otherwise.
+-% iter=scalar no. of interations used.
+-% corp= correlation matrix for parameters
+-% covp= covariance matrix of the parameters
+-% covr = diag(covariance matrix of the residuals)
+-% stdresid= standardized residuals
+-% Z= matrix that defines confidence region
+-% r2= coefficient of multiple determination
++% f = column vector of values computed: f = F(x,p).
++% p = column vector trial or final parameters. i.e, the solution.
++% kvg = scalar: = 1 if convergence, = 0 otherwise.
++% iter = scalar number of iterations used.
++% corp = correlation matrix for parameters.
++% covp = covariance matrix of the parameters.
++% covr = diag(covariance matrix of the residuals).
++% stdresid = standardized residuals.
++% Z = matrix that defines confidence region (see comments in the source).
++% r2 = coefficient of multiple determination.
+ %
+ % All Zero guesses not acceptable
+
+@@ -113,7 +119,7 @@
+ % 8) Change to more efficent algorithm of Bard for selecting epsL.
+ % 9) Tighten up memory usage by making use of sparse matrices (if
+ % MATLAB version >= 4.0) in computation of covp, corp, stdresid.
+-% Modified by Francesco Potorti
++% Modified by Francesco Potortì
+ % for use in Octave
+ %
+ % References:
More information about the Pkg-octave-commit
mailing list