Add a useful package (from Source forge) for octave

[CreaPhase.git] / octave_packages / data-smoothing-1.3.0 / doc-cache

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+# Created by Octave 3.6.1, Thu Mar 22 19:35:12 2012 UTC <root@brouzouf>
+# name: cache
+# type: cell
+# rows: 3
+# columns: 4
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 5
+ddmat
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 352
+ -- Function File: D = ddmat (X, O)
+     Compute divided differencing matrix of order O
+
+          Input
+               X:  vector of sampling positions
+
+               O:  order of diffferences
+
+          Output
+               D:  the matrix; D * Y gives divided differences of order
+               O
+
+     References:  Anal. Chem. (2003) 75, 3631.
+
+
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 47
+Compute divided differencing matrix of order O
+
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 13
+regdatasmooth
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 1939
+ -- Function File: [YHAT, LAMBDA] = regdatasmooth (X, Y, [OPTIONS])
+     Smooths the Y vs. X values of 1D data by Tikhonov regularization.
+     The smooth y-values are returned as YHAT. The regularization
+     parameter LAMBDA that was used for the smoothing may also be
+     returned.
+
+     Note:  the options have changed!  Currently supported input
+     options are (multiple options are allowed):
+
+    `"d", VALUE'
+          the smoothing derivative to use (default = 2)
+
+    `"lambda", VALUE'
+          the regularization paramater to use
+
+    `"stdev", VALUE'
+          the standard deviation of the measurement of Y; an optimal
+          value for lambda will be determined by matching the provided
+          VALUE with the standard devation of YHAT-Y; if the option
+          "relative" is also used, then a relative standard deviation
+          is inferred
+
+    `"gcv"'
+          use generalized cross-validation to determine the optimal
+          value for lambda; if neither "lambda" nor "stdev" options are
+          given, this option is implied
+
+    `"lguess", VALUE'
+          the initial value for lambda to use in the iterative
+          minimization algorithm to find the optimal value (default = 1)
+
+    `"xhat", VECTOR'
+          A vector of x-values to use for the smooth curve; must be
+          monotonically increasing and must at least span the data
+
+    `"weights", VECTOR'
+          A vector of weighting values for fitting each point in the
+          data.
+
+    `"relative"'
+          use relative differences for the goodnes of fit term.
+          Conflicts  with the "weights" option.
+
+    `"midpointrule"'
+          use the midpoint rule for the integration terms rather than a
+          direct sum; this option conflicts with the option "xhat"
+
+     Please run the demos for example usage.
+
+     References:  Anal. Chem. (2003) 75, 3631; AIChE J. (2006) 52, 325
+
+     See also: rgdtsmcorewrap, rgdtsmcore
+
+
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 17
+Smooths the Y vs.
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 10
+rgdtsmcore
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 1279
+ -- Function File: [YHAT, V] = rgdtsmcore (X, Y, D, LAMBDA, [OPTIONS])
+     Smooths Y vs. X values by Tikhonov regularization.  Although this
+     function can be used directly, the more feature rich function
+     "regdatasmooth" should be used instead.  In addition to X and Y,
+     required input includes the smoothing derivative D and the
+     regularization parameter LAMBDA.  The smooth y-values are returned
+     as YHAT.  The generalized cross validation variance V may also be
+     returned.
+
+     Note:  the options have changed!  Currently supported input
+     options are (multiple options are allowed):
+
+    `"xhat", VECTOR'
+          A vector of x-values to use for the smooth curve; must be
+          monotonically increasing and must at least span the data
+
+    `"weights", VECTOR'
+          A vector of weighting values for fitting each point in the
+          data.
+
+    `"relative"'
+          use relative differences for the goodnes of fit term.
+          Conflicts  with the "weights" option.
+
+    `"midpointrule"'
+          use the midpoint rule for the integration terms rather than a
+          direct  sum; this option conflicts with the option "xhat"
+
+     References:  Anal. Chem. (2003) 75, 3631; AIChE J. (2006) 52, 325
+
+     See also: regdatasmooth
+
+
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 13
+Smooths Y vs.
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 14
+rgdtsmcorewrap
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 485
+ -- Function File: CVE = rgdtsmcorewrap (LOG10LAMBDA, X, Y, D, MINCELL,
+          OPTIONS)
+ -- Function File: STDEVDIF = rgdtsmcorewrap (LOG10LAMBDA, X, Y, D,
+          MINCELL, OPTIONS)
+     Wrapper function for rgdtsmcore in order to minimize over  LAMBDA
+     w.r.t. cross-validation error OR the squared difference  between
+     the standard deviation of (Y-YHAT) and the given  standard
+     deviation.  This function is called from regdatasmooth.
+
+     See also: regdatasmooth
+
+
+
+
+
+# name: <cell-element>
+# type: sq_string
+# elements: 1
+# length: 68
+Wrapper function for rgdtsmcore in order to minimize over  LAMBDA
+w.
+
+
+
+
+