diff --git a/Scripts/2E_Move_Current_Demographic_Data_to_Current_Year.r b/Scripts/2E_Move_Current_Demographic_Data_to_Current_Year.r
index 22b909d..c645f2e 100644
--- a/Scripts/2E_Move_Current_Demographic_Data_to_Current_Year.r
+++ b/Scripts/2E_Move_Current_Demographic_Data_to_Current_Year.r
@@ -1,19 +1,79 @@
+library(tidyverse)
+#setwd("../") 
 #Script to increment the migration, and death data to start simulation in 2024, projecting 2025
-ODDS_MIGRATE <- readRDS("Data/Intermediate_Inputs/Migration_Trends/Migration_Age_Probablity_Zero_to_85.Rds")
-KEM_CURRENT <- readRDS("Data/Intermediate_Inputs/Starting_Demographic_Data_Sets_of_Monte_Carlo/2023_Starting_Kemmerer_Diamondville_Demographics_Matrix.Rds") 
-KEM_CURRENT_POP <- readRDS("Data/Cleaned_Data/Population_Data/RDS/Kemmerer_Diamondville_Population_Data.Rds") 
-num_migrated <- KEM_CURRENT_POP %>% filter(Year==2023) %>% pull(Migration) %>% abs
+ODDS_LEAVE <- readRDS("Data/Intermediate_Inputs/Migration_Trends/Migration_Age_Probablity_Zero_to_85.Rds")
+KEM_DEMOGRAPHIC <- readRDS("Data/Intermediate_Inputs/Starting_Demographic_Data_Sets_of_Monte_Carlo/2023_Starting_Kemmerer_Diamondville_Demographics_Matrix.Rds") 
+NUM_MIGRATED_OUT<- readRDS("Data/Cleaned_Data/Population_Data/RDS/Kemmerer_Diamondville_Population_Data.Rds") %>% filter(Year==2023) %>% pull(Migration) %>% abs
+
+MIGRATED_OUT <- function(KEM_CURRENT,NUM_MIGRATED_OUT,ODDS_MIGRATED){
+	POP_TOTAL <- sum(KEM_CURRENT)
+  if(POP_TOTAL>NUM_MIGRATED_OUT){
+	RES_MAT <- matrix(NA,nrow=POP_TOTAL,ncol=2)
+	RES_MAT[,2] <- c(rep(1,sum(KEM_CURRENT[,1])),rep(2,sum(KEM_CURRENT[,2])))
+	DEM_LIST <- as.vector(KEM_CURRENT)
+	ODDS_SET <- rep(ODDS_MIGRATED,2)
+	ODDS_RES <- matrix(NA,ncol=1,nrow=POP_TOTAL)
+	for(i in 1:172){
+		ST <- min(which(is.na(RES_MAT)))
+		NUM_REP <- DEM_LIST[i]
+		if(NUM_REP>0){
+			RES_MAT[ST:(NUM_REP+ST-1)] <-	rep(i,NUM_REP )
+			ODDS_RES[ST:(NUM_REP+ST-1)] <- rep(ODDS_SET[i],NUM_REP)
+		}
+	}
+	RES_MAT[,1] <-	RES_MAT[,1]-86*(RES_MAT[,2]-1)
+	NOT_MIGRATED <- RES_MAT[sample(1:nrow(RES_MAT),POP_TOTAL-NUM_MIGRATED_OUT,prob=1-ODDS_RES,replace=FALSE),]
+	if(POP_TOTAL-NUM_MIGRATED_OUT==1){
+		OUT <- as.matrix(t(NOT_MIGRATED),nrow=1,ncol=2)
+		rownames(OUT) <- OUT[1]-1
+		MALE_FEMALE <- OUT[2]
+		OUT[MALE_FEMALE] <- 1
+		OUT[-MALE_FEMALE] <- 0
+		OUT[1] <- 1
+	}else{
+		OUT <- table(NOT_MIGRATED[,1],NOT_MIGRATED[,2])
+		if(ncol(OUT)==1){
+			OUT_ORIG <- OUT
+			NEW_COL_INDEX <- as.character(which(!(c(1,2) %in% colnames(OUT) )))
+			OUT <- cbind(OUT,rep(0,nrow(OUT)))
+			colnames(OUT) <- c(colnames(OUT)[1],NEW_COL_INDEX)
+			OUT <- OUT[,c("1","2")]
+		}
+		rownames(OUT) <- as.numeric(rownames(OUT))-1
+	}
+
+		colnames(OUT) <- c("Num_Male","Num_Female" )
+	if(nrow(OUT)<86){
+		ZERO_ROWS <- 0:85
+		ZERO_ROWS <- ZERO_ROWS[!(0:85 %in% rownames(OUT))]
+		OUT <- rbind(OUT,matrix(0,nrow=length(ZERO_ROWS),ncol=2,dimnames=list(ZERO_ROWS,colnames(OUT))))
+		OUT <- OUT[as.character(sort(as.numeric(rownames(OUT)))),]
+	}
+  } else{
+	  OUT <- matrix(0,nrow=86,ncol=2,dimnames=list(0:85,colnames(KEM_CURRENT)))}
+	return(OUT)
+}
+ODDS_LEAVE <- readRDS("Data/Intermediate_Inputs/Migration_Trends/Migration_Age_Probablity_Zero_to_85.Rds")
+KEM_DEMOGRAPHIC <- readRDS("Data/Intermediate_Inputs/Starting_Demographic_Data_Sets_of_Monte_Carlo/2023_Starting_Kemmerer_Diamondville_Demographics_Matrix.Rds") 
+NUM_MIGRATED_OUT<- readRDS("Data/Cleaned_Data/Population_Data/RDS/Kemmerer_Diamondville_Population_Data.Rds") %>% filter(Year==2023) %>% pull(Migration) %>% abs
+
+
+start_time <- Sys.time()
+for(x in 1:round(10^6/23)){MIGRATED_OUT(KEM_DEMOGRAPHIC,NUM_MIGRATED_OUT,ODDS_LEAVE)}
+end_time <- Sys.time()
+end_time - start_time
+
+head(KEM_CURRENT)
 
 LENGTH <- length(KEM_CURRENT)
-
-for(x in 1:10^5){
+for(x in 1:10^6){
 KEM_NEW <- KEM_CURRENT
 for(i in 1:num_migrated){
 	MIGRATED <- sample(1:LENGTH,1,prob=1-(1-ODDS_MIGRATE)^KEM_CURRENT)
 	KEM_NEW[MIGRATED]
        	KEM_NEW[MIGRATED] <- KEM_NEW[MIGRATED]-1 
 }
-	if(x==1){RES <- KEM_CURRENT-KEM_NEW} else{RES<- cbind(RES,KEM_NEW-KEM_CURRENT)}
+#	if(x==1){RES <- KEM_CURRENT-KEM_NEW} else{RES<- cbind(RES,KEM_NEW-KEM_CURRENT)}
 }
 plot((rowMeans(RES)))