MATERNFIT is the jMatern module of jLab.

 MATERNFIT  Parametric spectral fit to the Matern form. [with A. Sykulski]
    MATERNFIT performs a parametric fit of the spectrum of a time series to
    that expected for a Matern process plus optional spin.  
    The Matern process plus spin has a spectrum given by, see MATERNSPEC, 
         SPP(F) = SIGMA^2 / [(F-NU)^2/LAMBDA^2 + 1]^ALPHA 
                                     / (LAMBDA * MATERNC(ALPHA))
    where SIGMA is the standard deviation, NU is a frequency shift, LAMBDA 
    is a damping coefficient, and ALPHA is 1/2 of the spectral slope.  The
    coefficient on the second line lets us parameterize the spectrum in 
    terms of the process variance SIGMA^2.
    The optimal parameters are found using a frequency-domain maximum
    likelihood method, accounting for both aliasing and spectral blurring.
    For further details on the parameter inference method method, see
      Sykulski, Olhede, Lilly, and Danioux (2016).  Lagrangian time series 
         models for ocean surface drifter trajectories. Journal of the 
         Royal Statisical Society, Series C. 65 (1): 29--50.
      Sykulski, Olhede, and Lilly (2016). The de-biased Whittle likelihood 
         for second-order stationary stochastic processes.  ArXiv preprint.
    For details on the Matern process and its spectrum, see:
      Lilly, Sykulski, Early, and Olhede, (2017).  Fractional Brownian
         motion, the Matern process, and stochastic modeling of turbulent 
         dispersion.  Nonlinear Processes in Geophysics, 24: 481--514.
    FIT=MATERNFIT(DT,Z,FO) where Z is a complex-valued time series, returns
    the result of a fitting the periodogram of Z to a background process
    having a non-shifted Matern form, fit over all frequencies. The range 
    of frequencies involved in the fit can be modified, as described below.
    DT is the sample interval, which has units of days, while FO is a
    signed reference frequency in units of radians per day.  FO is used in 
    determining search ranges and initial guesses.  In oceanographic
    applications, one would normally choose FO as the Coriolis frequency.
    The output argument FIT is a structure which will be described later.
    The default search ranges and initial guess values are as follows:
                     Low  Guess  High 
         SIGMA   =   [0      1    100] * STD(Z)
         ALPHA   =   [1/2    1     10] 
         LAMBDA  =   [1e-3  2e-3   10] * ABS(FO)
         NU      =   [0      0      0] * ABS(FO)
    These can be modified, as described below. 
    Output format
    The following parameters are output as fields of the structure FIT.
       SIGMA     Standard deviation of currents in cm/s
       ALPHA     Slope parameter 
       LAMBDA    Damping parameter in rad / day
       NU        Oscillation frequency in rad /day
       RANGE     Ranges of fit search for each parameter
       PARAMS    Sub-structure with fields described below
    The associated spectra can be then created from SIGMA, ALPHA, LAMBDA, 
    and NU using MATERNSPEC. 
    RANGE is substructure with fields SIGMA, ALPHA, LAMBDA, and NU, such 
    that RANGE.SIGMA specifies the *dimensional* values of the associated
    range and initial guess with format [MIN GUESS MAX], and so forth for 
    all the other parameters. 
    PARAMS is a substructure containing various parameter values
    characterizing the fit itself: 
       PARAMS.DT      Sample rate, as input to MATERNFIT
       PARAMS.FO      Reference frequency, as input to MATERNFIT
       PARAMS.A       Index into first frequency F(A) used in the fit
       PARAMS.B       Index into last frequency F(B) used in the fit  
       PARAMS.P       Number of free parameters used in the fit 
       LIKE           Negative of the log-likelihood 
       AICC           Akaike Information Criterion, corrected version 
       ERR            Normalized error of fit to log spectra 
       EXITFLAG       The exit flag from the optimization routine
       ITER           The number of iterations in the optimization routine
       PARAMS.SIDE    String specifying frequency side options
       PARAMS.ALG     String specifying algorithm options
       PARAMS.VER     String specifiying raw or difference option
       PARAMS.CORES   String specifying series or parallel computation
    These parameters are described in more detail below.
    Multiple input time series
    FIT=MATERNFIT(DT,Z,FO) may have Z being a matrix with N columns, or a 
    cell array of N different time series.  In both of these cases, DT and 
    FO may be scalars or length N arrays.
    In these cases, the fields SIGMA, ALPHA, LAMBDA, and NU of FIT will 
    also be arrays with N elements, as will LIKE, AICC, ERR, and EXITFLAG. 
    The subfields of RANGE will all be N x 3 arrays.  In PARAMS, the fields
    DT, FO, A, and B will all be length N.   
    Specifiying frequencies
    MATERNFIT(DT,Z,FO,RA,RB), where RA and RB are both real-valued scalars,
    applies the fit to only frequencies in the range
                ABS(FO)*RA < F < ABS(FO)*RB
    with the default behavior corresponding to MATERNFIT(DT,Z,FO,0,INF).
    Thus RA is the smallest permissible ratio of F to the reference 
    frequency, while RB is similarly the largest permissible ratio.
    MATERNFIT(DT,Z,FO,RA,[RB,RN]) also works, where the fifth argument is
    an array of length two. In this case the fit is applied to the range
                ABS(FO)*RA < F < MIN( ABS(FO)*RB, PI/DT*RN )
    RB is the largest permissible ratio of F to the reference frequency, 
    while RN is the largest permissible ratio of F to the Nyquist PI/DT.  
    The fit extends to the smaller of these two frequencies.  
    If RA and RB are imaginary numbers, rather than real numbers, then 
    the fit is only applied to frequencies in the range
                IMAG(RA) < F < IMAG(RB)
    that is, the range is found without scaling by the reference frequency. 
    MATERNFIT can create the fit by utilizing both positive and negative 
    frequency sides of the spectrum, the default behavior, or to only one 
    side (plus the zero frequency). This is modified as follows:
       MATERNFIT(...,'both',...), the default, uses both sides.
       MATERNFIT(...,'positive',...), uses the side where F/FO is positive.
       MATERNFIT(...,'negative',...), uses the side where F/FO is negative.
    Thus, changing the sign of the reference frequency also changes the 
    side of the spectrum to be fit using the 'postive' or 'negative' flags.
    Parameter range specification
    The default search ranges and guess values can be modified.  As an 
    example, to modify the default range and guess for the SIGMA parameter
    corresponding to the background flow, use
        MATERNFIT(...,'range.sigma',[MIN GUESS MAX],...)                   
    and so forth for other parameters. SIGMA ranges input to MATERNFIT 
    represent *fractions* of the total signal standard deviation.  Thus 
        MATERNFIT(...,'range.sigma',[0 1 100],...)
    corresponds to the default setting.  The upper limit is set very high
    because occasionally an optimum spectral fit is found that has much 
    larger total variance than the signal. 
    Similarly, ranges of LAMBDA and NU are nondimensional values representing
    fractions of the magnitude of the reference frequency ABS(FO).  Thus 
        MATERNFIT(...,'range.lambda',[1/1000 2/1000 1],...)
    corresponds to the default range for LAMBDA. 
    The slope parameter ALPHA can take on a value of no less than 1/2, so
    the lower range for ALPHA cannot be less than 1/2.
    This approach can be used to omit parameters from the fit, by setting
    the MIN, GUESS, and MAX values to be identical.  For example,  
       MATERNFIT(...,'range.alpha',[2 2 2]) 
    sets the ALPHA parameter to a value of 2.  Fixed parameters are then 
    not included in the optimization, thus speeding up the fit.  
    Parameter value specification
    Parameters can also be set to particular values for each time series. 
    This is done by setting the 'value' field as follows
    and so forth for the other parameters.  
    Here SIGMA is an array of the same length as the number of time series
    in Z.  Thus SIGMA is a scalar if Z is a single array, an array of
    LENGTH(Z) is Z is a cell array, or of SIZE(Z,2) if Z is a matrix. 
    Note that the values specified in this way are actual dimensional 
    values, not nondimensional values as with setting the range. 
    This approach works by internally setting the dimension MIN, GUESS, and
    MAX to the value specified for each time series, overriding the default 
    choices. This will be reflected in the output RANGE fields. 
    If both ranges and values are specified for the same parameter, the
    value settings take precedence.
    Numerical options
    MATERNFIT has options for specifying numerical details of the fit and 
    the optimization algorithm. 
    MATERNFIT can use one of two different optimization algorithms.
      MATERNFIT(...,'bnd',...), the default, uses FMINSEARCHBND by J. 
        D'Errico included with JLAB in accordance with its license terms. 
        This in turn calls Matlab's FMINSEARCH using Nelder-Mead.
      MATERNFIT(...,'con',...) alternately uses FMINCON, using the default
        interior-point algorithm.  This requires Matlab's Optimization 
        Toolbox to be installed.  Again, this is mainly for testing.
    In tests, FMINCON is generally faster, and most of the fits agree
    closely with those using FMINSEARCHBND.  However, occasionally FMINCON
    produces fits that are significantly worse than those obtained from 
    FMINSEARCHBND, which is why the latter is preferred by default.
    MATERNFIT can employ two different versions of the fit. 
      MATERNFIT(...,'difference',...) estimates the Matern parameters by 
        fitting the first difference of the time series to the first 
        difference of a Matern process.  This amounts to a form of pre-
        whitening, and is the default behavior when a taper is not input.
      MATERNFIT(...,'raw',...) fits the time series directly to a Matern. 
        This is the default behavior when a taper *is* input.
    These choices are reflected in the output fields PARAMS.ALG and 
    PARAMS.VER, respectively.
    The default behavior of fitting the first difference of the spectrum 
    is usually sufficient to account for spectral blurring.  For very steep 
    spectra or those with a very large dynamic range, this is no longer the
    case, because leakage from high-energy portions of the spectra will 
    obscure the structure of low-energy portions. 
    To addess this, MATERNFIT can optionally perform the fit by fitting 
    to the tapered and aliased spectrum, correctly accounting for the 
    influence of tapering.  This is accomplished with 
    where PSI is a data taper of the same length as Z.  If Z is a cell
    array, then PSI is a cell array of data tapers having the same length
    as the components of Z.  PSI is typically computed by SLEPTAP.
    When a taper is input, the default behavior is *not* to difference 
    the time series, corresponding to the 'raw' option.  If both a taper
    and the 'difference' flag are both input, then the taper length must 
    be one less than the data length.  
    While the maximum likelikehood method is not about finding the best 
    fit in a least squares sense, a measure of the mean squared error 
    provides a useful measure of evaluating the degree of misfit.
    The error ERR returned by MATERNFIT is the squared difference between 
    the *natural log* of the periodogram and that of the fit spectrum, 
    summed over all frequencies used in the fit, and divided by the sum of 
    the squared natural log of the periodogram over the same frequencies.
    The error is computed over the inertial side, anti-inertial side, or 
    both sides, depending on which frequency range is used for the fit. 
    When the 'difference' behavior is employed, as is the default, ERR will
    reflect the error between the periodogram of the first difference of 
    the time series and the spectrum of the first difference of the fit.
    With Matlab's Parallel Computing toolbox installed, when Z is a cell 
    array or a matrix, MATERNFIT(DT,Z,'parallel') will loop over the 
    elements of Z using a parallel "parfor" loop to speed things up.
    This choice is reflected in the output field PARAMS.CORES, which 
    will take on the values 'series' (the default) or 'parallel'.
    'maternfit --t' runs a test.
    Usage: fit=maternfit(dt,z);
    This is part of JLAB --- type 'help jlab' for more information
    (C) 2014--2017 J.M. Lilly and A.M. Sykulski
                                 --- type 'help jlab_license' for details

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