From 14ec98c9bfc49f963e30159dc7db9f554088fb44 Mon Sep 17 00:00:00 2001
From: hannajankowski <hkj@yorku.ca>
Date: Thu, 9 Jun 2022 17:57:31 -0400
Subject: Testing testing 123

---
 R/WP_unknown.R | 47 +++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 47 insertions(+)
 create mode 100644 R/WP_unknown.R

(limited to 'R/WP_unknown.R')

diff --git a/R/WP_unknown.R b/R/WP_unknown.R
new file mode 100644
index 0000000..a450b54
--- /dev/null
+++ b/R/WP_unknown.R
@@ -0,0 +1,47 @@
+#' WP method background function WP_unknown
+#'
+#' This is a background/internal function called by \code{WP}.  It computes the maximum likelihood estimator of R0 assuming that the serial distribution is unknown but comes from a discretized gamma distribution.  The function then implements a simple grid search algorithm to obtain the maximum likelihood estimator of R0 as well as the gamma parameters.
+#'
+#' @param NT vector of case counts
+#' @param B length of grid for shape and scale (grid search parameter)
+#' @param shape.max maximum shape value (grid search parameter)
+#' @param scale.max maximum scale value (grid search parameter)
+#' @param tol cutoff value for cumulative distribution function of the serial distribution, defaults to 0.999
+#' @return The function returns \code{Rhat}, the maximum likelihood estimator of R0, as well as the maximum likelihood estimator of the discretized serial distribution given by \code{p} (the probability mass function) and \code{range.max} (the distribution has support on the integers one to \code{range.max}).  The function also returns \code{resLL} (all values of the log-likelihood) at \code{shape} (grid for shape parameter) and at \code{scale} (grid for scale parameter), as well as \code{resR0} (the full vector of maximum likelihood estimators), \code{JJ} (the locations for the likelihood for these), and \code{J0} (the location for the maximum likelihood estimator \code{Rhat}).  If \code{JJ} and \code{J0} are not the same, this means that the maximum likelihood estimator is not unique. 
+#'
+#' @export
+
+WP_unknown		<-	function(NT, B=100, shape.max=10, scale.max=10, tol=0.999){
+	
+	shape		<-	seq(0, shape.max, length.out=B+1)
+	scale		<-	seq(0, scale.max, length.out=B+1)
+	shape		<-	shape[-1]
+	scale		<-	scale[-1]
+		
+	resLL		<-	matrix(0,B,B)
+	resR0		<-	matrix(0,B,B)
+		
+	for(i in 1:B){
+	for(j in 1:B){	
+		range.max	<-	ceiling(qgamma(tol, shape=shape[i], scale=scale[j]))
+		p			<-	diff(pgamma(0:range.max, shape=shape[i], scale=scale[j]))
+		p			<-	p/sum(p)
+		mle			<-	WP_known(NT, p)
+		resLL[i,j]	<-	computeLL(p, NT, mle$R)
+		resR0[i,j]	<-	mle$R
+	}		
+#		print(i)
+	}
+	
+	J0			<-	which.max(resLL)
+	R0hat		<-	resR0[J0]	
+	JJ			<-	which(resLL==resLL[J0], arr.ind=TRUE)
+#	JJ			<-	which(resLL==max(resLL), arr.ind=TRUE)
+	range.max	<-	ceiling(qgamma(tol, shape=shape[JJ[1]], scale=scale[JJ[2]]))
+	p			<-	diff(pgamma(0:range.max, shape=shape[JJ[1]], scale=scale[JJ[2]]))
+	p			<-	p/sum(p)
+	
+	return(list(Rhat=R0hat, J0=J0, ll=resLL, Rs=resR0, scale=scale, shape=shape, JJ=JJ, p=p, range.max=range.max))
+}
+
+
-- 
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