

   CCoonnttrrooll VVaalluueess ffoorr llmmee FFiitt

        lmeControl(maxIter, msMaxIter, tolerance, niterEM, msTol,
                   msScale, msVerbose, returnObject, gradHess, apVar,
                   .relStep, natural)

   AArrgguummeennttss::

    maxIter: maximum number of iterations for the `lme' opti-
             mization algorithm. Default is 50.

   msMaxIter: maximum number of iterations for the `ms' opti-
             mization step inside the `lme' optimization.
             Default is 50.

   tolerance: tolerance for the convergence criterion in the
             `lme' algorithm. Default is 1e-6.

    niterEM: number of iterations for the EM algorithm used to
             refine the initial estimates of the random effects
             variance-covariance coefficients. Default is 25.

      msTol: tolerance for the convergence criterion in `ms',
             passed as the `rel.tolerance' argument to the
             function (see documentation on `ms'). Default is
             1e-7.

    msScale: scale function passed as the `scale' argument to
             the `ms' function (see documentation on that func-
             tion). Default is `lmeScale'.

   msVerbose: a logical value passed as the `trace' argument to
             `ms' (see documentation on that function). Default
             is `FALSE'.

   returnObject: a logical value indicating whether the fitted
             object should be returned when the maximum number
             of iterations is reached without convergence of
             the algorithm. Default is `FALSE'.

   gradHess: a logical value indicating whether numerical gra-
             dient vectors and Hessian matrices of the log-
             likelihood function should be used in the `ms'
             optimization. This option is only available when
             the correlation structure (`corStruct') and the
             variance function structure (`varFunc') have no
             "varying" parameters and the `pdMat' classes used
             in the random effects structure are `pdSymm' (gen-
             eral positive-definite), `pdDiag' (diagonal),
             `pdIdent' (multiple of the identity),  or `pdComp-
             Symm' (compound symmetry). Default is `TRUE'.

      apVar: a logical value indicating whether the approximate
             covariance matrix of the variance-covariance
             parameters should be calculated. Default is
             `TRUE'.

   .relStep: relative step for numerical derivatives calcula-
             tions. Default is `.Machine$double.eps^(1/3)'.

    natural: a logical value indicating whether the `pdNatural'
             parametrization should be used for general posi-
             tive-definite matrices (`pdSymm') in `reStruct',
             when the approximate covariance matrix of the
             estimators is calculated. Default is `TRUE'.

   DDeessccrriippttiioonn::

        The values supplied in the function call replace the
        defaults and a list with all possible arguments is
        returned. The returned list is used as the `control'
        argument to the `lme' function.

   VVaalluuee::

        a list with components for each of the possible argu-
        ments.

   AAuutthhoorr((ss))::

        Jose Pinheiro and Douglas Bates

   SSeeee AAllssoo::

        `lme', `ms', `lmeScale'

   EExxaammpplleess::

        # decrease the maximum number iterations in the ms call and
        # request that information on the evolution of the ms iterations be printed
        lmeControl(msMaxIter = 20, msVerbose = TRUE)

