maxlik.src

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**  _max_GradCheckTol   - scalar, if nonzero and if proc's exist for
**               computing the gradient or Hessian, their calculations
**               will be compared with numerical gradients and Hessians
**               in order to determine their correctness.
**
**   ----- Convergence Criteria -----
**
**  _max_GradTol  - scalar, convergence tolerance for gradient of estimated
**             coefficients.  Default = 1e-5.  When this criterion has been
**             satisifed OPTMUM will exit the iterations.
**
**  _max_MaxIters - scalar, maximum number of iterations.
**
**  _max_MaxTime - scalar, maximum time in iterations in minutes.
**             Default = 1e+5, about 10 weeks.
**
**   ----- Data -----
**
**  _max_Active - vector, 0 = fixed coefficient, 1 = active coefficient.
**                By default all coefficients are active.
**
**  __weight - vector, frequency of observations.  By default all
**             observations have a frequency of 1.  zero frequencies
**             are allowed.  It is assumed that the elements of __weight
**             sum to the number of observations.
**
**  _max_Lag   - scalar, if the function includes lagged values of the
**             variables _max_Lag may be set to the number of lags.  When
**             _max_Lag is set to a nonzero value then __row is set to 1
**             (that is, the function must evaluated one observation at a
**             time), and MAXLIK will pass a matrix to the user-provided
**             function and gradient procedures.  The first row in this
**             matrix will be (i - _max_Lag)-th observation and the last
**             row will be the i-th observation.  The read loop will begin
**             with the (_max_Lag+1)-th observation.  Default = 0.
**
**  _max_NumObs  - scalar, number of cases in the data set that was analyzed.
**
**  _max_ParNames - Kx1 character vector, parameter labels.
**
**  __row    - determines the number of rows in the data set to be passed
**             to the user-provided procedures. Default = 0.
**
**  __rowfac - If MAXLIK fails due to insufficient memory while attempting
**             to read a GAUSS data set, then __rowfac may be set to some
**             value between 0 and 1 to read a proportion of the original
**             number of rows of the GAUSS data set.
**
**   ----- Miscellaneous -----
**
**  __title  -  title of run
**
**  _max_Diagnostic - scalar. If 1, current estimates ("coeffs"),
**                   gradient ("gradient"), direction ("direct"),
**                   function value ("function"), Hessian ("Hessian"),
**                   and step length computed in the line search ("step")
**                   are printed to the screen.  If 2, they are
**                   stored in _max_Diagnostic using VPUT.  Use
**                   VREAD to extract.  If 3, both 1 and 2 occur.
**
**  _max_IterData - 3x1 vector, contains information about the iterations.
**             The first element contains the # of iterations , the second
**             element contains the elapsed time in minutes of the iterations,
**             and the third element contains a character variable indicating
**             the type of covariance matrix of the parameters.
**
**  _max_Key   - scalar, controls keyboard capture.  Useful for recursively
**             nested version of MAXLIK.  Setting _max_key = 0 for the
**             nested versions will turn off their key board captures
**             permitting the outside version to retain control of the
**             keyboard.
**
**-------------------**------------------**-------------------**-----------**
**-------------------**------------------**-------------------**-----------**
**
**     Procedure For Computing Likelihood Function
**
**           The user must provide a procedure for computing the
**       log-likelihood for either one observation, or for a matrix of
**       observations.  The procedure must have two input arguments,
**       first, a vector of parameter values, and second, one or more rows
**       of the data matrix.  The output argument is the log-likelihood
**       for the observation or observations in the second argument
**       evaluated at the parameters values in the first argument.
**           Suppose that the function procedure has been named fct,
**       the following considerations apply:
**
**       FORMAT
**               logl=fct(x,y)
**
**       INPUT
**               x - vector of parameters of model
**
**               y - one or more rows of the data set (if the data set has
**                   been transformed, or if vars /= 0, i.e., there is
**                   selection, then y is a transformed, selected observation)
**                   if __row == 1,  one row of the data set
**                   if __row >= 2,  if data set is stored in memory then
**                                   all of the data set will be passed to FCT;
**                                   if data set is stored in GAUSS data file
**                                   then __row will be passed to passed to
**                                   FCT.
**                   if __row <= 0,  For data set is stored in memory same as
**                                   __row >= 2,
**                                   for GAUSS data file the maximum number of
**                                   rows that will fit in memory will be
**                                   computed by MAXLIK.
**                  if _max_Lag >= 1,  a matrix of observations, the first is
**                                  the i-_max_Lag row, and the final row is
**                                  the i-th row.
**
**       OUTPUT
**               logl - the log-likelihood
**                      if __row == 1 or _max_Lag >= 1,  a scalar value for
**                      a given observation, otherwise a vector of
**                      log-likelihoods.
**
**
**       REMARKS
**
**           If you have written the procedure such that it must compute
**        the log-likelihood of one observation at a time then you
**        must set __row = 1.  But if you are able to write the procedure
**        so that a vector of log-likelihoods may be returned then set
**        __row=0; If you are getting "insufficient memory" messages when the
**        data are being read from a GAUSS data file then either set __row ==1
**        or to some positive value.
**           Also, if the data set is stored in a GAUSS data set and the
**        selected data set will fit into memory, then MAXLIK will read
**        it in and store it before beginning the iterations.  In this
**        case the setting of __row will follow the rules of a data set
**        stored in memory.
**           Significant reduction in computation time may be achieved
**        when the data set can be stored in memory and procedure is
**        written to compute vectors of log-probabilities.
**
**-------------------**------------------**-------------------**-----------**
**-------------------**------------------**-------------------**-----------**
**
**    Calling MAXLIK Recursively
**
**    The procedure that computes the log-likelihood may itself call
**    MAXLIK.   When calling MAXLIK recursively the following
**    considerations apply:
**
**        If a data set is being analyzed and it is to be transformed
**    or deleted for missing data or cases are to be selected, then
**    this can be done only on the outermost version of MAXLIK, i.e.,
**    the version called in the original command file.  Variable
**    selection (as opposed to case selection) can be done on any
**    level through the second argument in the call to each version
**    of MAXLIK.  Data sets can be opened by nested versions of MAXLIK.
**       If a nested version of MAXLIK is going to use the data set
**    opened by the outer version of MAXLIK then pass a null string
**    (i.e., "") in the first argument in the call.  If it is going
**    to analyze a different data set from the outer version then
**    pass it the data set name in a string.  You may also load and
**    store a data set in memory in the command file and pass it as
**    the first argument in the nested call to MAXLIK.
**
**        Before the call to the nested version of MAXLIK, the global
**    variables may be re-set by calling MAXCLR.  You must not use
**    MAXSET because that will clear information about the data sets
**    opened and processed in the outer version.  The only differences
**    between MAXSET and MAXCLR are references to these globals.
**
**         You may also want to disable the keyboard control of the
**    nested versions.  This is done by setting the global _max_key = 0
**    after the call to MAXCLR and before the call to the nested MAXLIK.
**
*/

/*-------------------**------------------**-------------------**-----------**
**-------------------**------------------**-------------------**-----------*/

/*  SOURCE CODE  */

#include gauss.ext
#include maxlik.ext

external proc indices;

proc (5) = maxlik(dataset,var,lfct,start);
    local x,f,g,h,retcode;
    local Lmlcpvcp, Lmlhsvcp, Lmlfhess, Lmlitdta, Lmldiag;

   if _max_GradMethod == 0;
        _max_eps2 = __macheps^(1/3);
    else;
        _max_eps2 = __macheps^(1/2);
    endif;
    _max_eps3 = __macheps^(1/3);

    { x,f,g,h,retcode,Lmlfhess,Lmlitdta,Lmlcpvcp,Lmlhsvcp,_max_dat,
       _max_NumObs,_max_row,_max_dsn,Lmldiag } = _max(dataset,var,lfct,start,
    _max_Algorithm,
    _max_Diagnostic,
    _max_GradCheckTol,
    _max_LineSearch,
    _max_CovPar,
    _max_GradMethod,
    _max_GradStep,
    _max_Delta,
    _max_Extrap,
    _max_GradProc,
    _max_GradTol,
    _max_HessProc,
    _max_Interp,
    _max_Key,
    _max_Lag,
    _max_MaxIters,
    _max_MaxTime,
    _max_MaxTry,
    _max_NumObs,
    _max_ParNames,
    _max_RandRadius,
    _max_Options,
    _max_UserSearch,
    _max_UserNumGrad,
    _max_UserNumHess,
    _max_Active,
    _max_dat,
    _max_dsn,
    _max_row,
    __altnam,
    __output,
    __row,
    __title,
    __weight
    );

    _max_FinalHess = Lmlfhess;
    _max_IterData = Lmlitdta;
    _max_XprodCov = Lmlcpvcp;
    _max_HessCov = Lmlhsvcp;
    _max_Diagnostic = Lmldiag;

    retp(x,f,g,h,retcode);
endp;


proc(0) = maxset;

    gausset;
    _max_Options = 0;
    _max_Algorithm = 2;
    _max_LineSearch = 2;
    _max_CovPar = 1;
    _max_GradMethod = 1;
    _max_ParNames = 0;     /* parameter names */
    _max_GradTol = 1e-5;   /* convergence tolerance for gradient */
    _max_HessProc = 0;     /* procedure to compute hessian */
    _max_GradProc = 0;     /* procedure to compute gradient */
    _max_MaxIters = 1e+5;  /* maximum number of iterations */
    _max_IterData = {0,0,0}; /* elapsed time, # of iters, cov method */
    _max_RandRadius = .01; /* random line search */
    _max_UserSearch = 0;   /* interactive line search */
    _max_UserNumGrad = 0;
    _max_UserNumHess = 0;
    _max_Extrap = 2.0;   /* extrapolation constant */
    _max_interp = 0.25;  /* interpolation constant */
    _max_Delta = .1;
    _max_MaxTry = 100;
    _max_Lag = 0;         /* number of lags in model */
    _max_FinalHess = 0;
    _max_NumObs = 0;      /* number of observations */
    _max_HessCov = {.};     /* info matrix v-c matrix of par's */
    _max_XprodCov = {.};    /* cross proc matrix v-c matrix of par's  */
    _max_key = 1;
    _max_MaxTime = 1e5;   /* maximum time for bootstrapping */
    _max_Active = 1;
    _max_GradStep = {.};      /* size of increment for computing gradient */
    _max_GradCheckTol = 0;
    _max_Diagnostic = {.};
    _max_Alpha = .05;
    _max_Switch = 0;

    _max_BayesAlpha = 1.4;
    _max_PriorProc = {.};
    _max_CrossTab = { . };  /* crosstab of coef's output from cvhist */
    _max_CutPoint = { . };  /* cutting points for _max_xtab */
    _max_Increment = 0;     /* if nonzero, histogram increments */
    _max_Center = 0;        /* if nonzero, center points for histogram */
    _max_Width = 2;         /* width of histogram = _max_Width * sd's */
    _max_NumSample = 50;   /* bootstrap sample size */
    _max_NumCat = 16;       /* # of cat's for bootstrapped histogram */
    _max_Select = {.};

    _max_dsn = "";
    _max_dat = { . };
    _max_row = 0;

endp;

proc(0) = maxclr;

    gausset;
    _max_Options = 0;
    _max_Algorithm = 2;
    _max_LineSearch = 2;
    _max_CovPar = 1;
    _max_GradMethod = 1;
    _max_ParNames = 0;     /* parameter names */
    _max_GradTol = 1e-5;   /* convergence tolerance for gradient */
    _max_HessProc = 0;     /* procedure to compute hessian */
    _max_GradProc = 0;     /* procedure to compute gradient */
    _max_MaxIters = 1e+5;  /* maximum number of iterations */
    _max_IterData = {0,0,0}; /* elapsed time, # of iters, cov method */
    _max_RandRadius = .01; /* random line search */
    _max_UserSearch = 0;   /* interactive line search */
    _max_UserNumGrad = 0;
    _max_UserNumHess = 0;
    _max_Extrap = 2.0;   /* extrapolation constant */
    _max_interp = 0.25;  /* interpolation constant */
    _max_Delta = .1;
    _max_MaxTry = 100;
    _max_Lag = 0;         /* number of lags in model */
    _max_FinalHess = 0;
    _max_NumObs = 0;      /* number of observations */
    _max_HessCov = 0;     /* info matrix v-c matrix of par's */
    _max_XprodCov = 0;    /* cross proc matrix v-c matrix of par's  */