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# doc-cache created by Octave 4.0.0
# name: cache
# type: cell
# rows: 3
# columns: 4
# name: <cell-element>
# type: sq_string
# elements: 1
# length: 5
ddmat


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# type: sq_string
# elements: 1
# length: 330
 -- 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>
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Compute divided differencing matrix of order O



# name: <cell-element>
# type: sq_string
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# length: 13
regdatasmooth


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 -- 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
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Smooths the Y vs.



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# type: sq_string
# elements: 1
# length: 10
rgdtsmcore


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# length: 1276
 -- 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
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# length: 13
Smooths Y vs.



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# type: sq_string
# elements: 1
# length: 14
rgdtsmcorewrap


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 -- 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>
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Wrapper function for rgdtsmcore in order to minimize over LAMBDA w.r.t.