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#' Parameter Estimation for Persistence and Search Proficiency
#'
#' Finds Maximum Likelihood Estimates Weibull persistence parameters,
#' and for exponentially decreasing search proficiency.
#'
#' @param rd list output from acme::read.data()
#' @param fname file name to which the output parameters are saved
#' @return \code{acme.est} returns a list with the following components:
#' \item{params}{5-element vector: alpha and rho parameters for the
#' Weibull persistence distribution, a and b parameters for the
#' exponentially decreasing search proficiency, and bt as the bleed-through
#' rate}
#' \item{info}{list of select system information inherited from
#' acme::read.data() output}
#'
# Model Implementation:
# acme.est() Return and store in "acme.est" vector of param ests
##################################################################
# Five Parameter Estimates
#
acme.est <- function(rd, fname="acme.est") {
if(missing(rd))
print("Usage: acme.est(rd, <output.file>)");
scav <- mle.wei(rd, v=TRUE);
srch <- mle.srch(rd, v=TRUE);
est <- list(params=c(scav$alp, scav$rho,
a=srch$a.hat, b=srch$b.hat, bt=srch$bt.hat),
info=rd$Info);
save(est, file=fname);
return(est);
}
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