\name{bildIntegrate} \alias{bildIntegrate} \title{ Auxiliary for Controlling "bild" Fitting} \description{Auxiliary function as user interface for \code{bild} fitting } \usage{bildIntegrate(li=-4,ls=4, epsabs=.Machine$double.eps^.25, epsrel=.Machine$double.eps^.25,limit=100,key=6,lig=-4,lsg=4) } \arguments{ \item{li}{lower limit of integration for the log-likelihood.} \item{ls}{upper limit of integration for the log-likelihood.} \item{epsabs}{absolute accuracy requested.} \item{epsrel}{relative accuracy requested.} \item{key}{integer from 1 to 6 for choice of local integration rule for number of Gauss-Kronrod quadrature points. A gauss-kronrod pair is used with: \cr 7 - 15 points if key = 1, \cr 10 - 21 points if key = 2,\cr 15 - 31 points if key = 3,\cr 20 - 41 points if key = 4,\cr 25 - 51 points if key = 5 and \cr 30 - 61 points if key = 6.} \item{limit}{integer that gives an upperbound on the number of subintervals in the partition of (\code{li},\code{ls}), limit.ge.1.} \item{lig}{lower limit of integration for the gradient.} \item{lsg}{upper limit of integration for the gradient.} } \details{ \code{bildIntegrate} returns a list of constants that are used to compute integrals based on a Fortran-77 subroutine \code{dqage} from a Fortran-77 subroutine package \code{QUADPACK} for the numerical computation of definite one-dimensional integrals. The subroutine \code{dqage} is a simple globally adaptive integrator in which it is possible to choose between 6 pairs of Gauss-Kronrod quadrature formulae for the rule evaluation component. The source code \code{dqage} was modified and re-named \code{dqager}, the change was the introduction of an extra variable that allow, in our Fortran-77 subroutines when have a call to \code{dqager}, to control for which parameter the integral is computed. For given values of \code{li} and \code{ls}, the above-described numerical integration is performed over the interval (\code{li}*\eqn{\sigma}, \code{ls}*\eqn{\sigma}), where \eqn{\sigma=\exp(\omega)/2} is associated to the current parameter value \eqn{\omega} examined by the \code{optim} function. In some cases, this integration may generate an error, and the user must suitably adjust the values of \code{li} and \code{ls}. In case different choices of these quantities all lead to a successful run, it is recommended to retain the one with largest value of the log-likelihood. Integration of the gradient is regulated similarly by \code{lig} and \code{lsg}. For datasets where the individual profiles have a high number of observed time points (say, more than 30), use \code{bildIntegrate} function to set the integration limits for the likelihood and for the gradient to small values than the default ones, see the example of \code{\link{locust}} data. If fitting procedure is complete but when computing the information matrix some NaNs are produced, the change of the default values for the gradient integration limits (\code{lig} and \code{lsg}) in \code{bildIntegrate} function might solve this problem. } \value{A list with the arguments as components.} \seealso{\code{\link{bild-class}}} \examples{ \donttest{ #### data=locust, dependence="MC2R" str(locust) Integ <- bildIntegrate(li=-2.5,ls=2.5, lig=-2.5, lsg=2.5) locust2r_feed1 <- bild(move~(time+I(time^2))*sex, data=locust, start=NULL, trace=TRUE, subSET=feed=="1", aggregate=sex, dependence="MC2R", integrate=Integ) summary(locust2r_feed1) getAIC(locust2r_feed1) getLogLik(locust2r_feed1) plot(locust2r_feed1) }} \keyword{function}