--- a
+++ b/man/Generate.Accrual.Rd
@@ -0,0 +1,37 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/accrual.R
+\name{Generate.Accrual}
+\alias{Generate.Accrual}
+\title{Create An AccrualGenerator using a power law recruitment}
+\usage{
+Generate.Accrual(start.date, end.date, k, deterministic = FALSE,
+  rec.start.date = NULL)
+}
+\arguments{
+\item{start.date}{The start of the subject accrual period}
+
+\item{end.date}{The date the last subject is accrued so \code{B} = 
+\code{end.date} - \code{start.date} unless \code{rec.start.date} is used see 
+below}
+
+\item{k}{The non-uniformity accrual parameter}
+
+\item{deterministic}{Logical, if FALSE then the recruitment times 
+are non-stochastically chosen so that their cumulative distribution function is \code{G(t)}
+otherwise they are generated by sampling random variables with a cdf \code{G(t)}}
+
+\item{rec.start.date}{If this argument is used the subjects are still recruited between 
+start.date and end.date but they follow the cdf \code{G(t)=(t^k-L^k)/(B^k-L^k)} where
+\code{t} is in \code{[L,B]} and \code{B = end.date - rec.start.date} and \code{L = start.date- rec.start.date}.}
+}
+\value{
+An AccrualGenerator object which generates the required subject accruals
+}
+\description{
+Subjects are accrued according to the c.d.f 
+\code{G(t)=t^k/B^k} where \code{k} is a parameter, 
+\code{t} is the time and \code{B} is the recruitment period. 
+ 
+See the predict from data vignette for further details
+}
+