version 0.50-2

DESCRIPTION

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+Package: bivpois
+Title: Bivariate Poisson Models Using The EM Algorithm
+Version: 0.50-2
+Date: 2005-08-25
+Depends: R (>= 2.0.1)
+Author: Dimitris Karlis and Ioannis Ntzoufras
+Description: Functions for fitting Bivariate Poisson Models using the EM algorithm. Details can be found in Karlis and Ntzoufras (2003, RSS D & 2004,AUEB Technical Report)
+Maintainer: Ioannis Ntzoufras <ntzoufras@aueb.gr>
+License: GPL (version 2 or later) 
+URL: http://www.stat-athens.aueb.gr/~jbn/papers/paper14.htm
+Packaged: Wed Aug 31 16:13:32 2005; admin

R/bivpois.table.R

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+"bivpois.table" <-
+function(x, y, lambda = c(1, 1, 1))
+{
+# ------------------------------------------------------------------------------
+# Karlis and Ntzoufras (2003, 2004)
+# EM algorithms for Bivariate Poisson Models
+# ------------------------------------------------------------------------------
+# x     : 1st count variable
+# y     : 2nd count variable
+# lambda: parameters of the bivariate poisson distribution.
+# ------------------------------------------------------------------------------
+
+	j<-0
+	n <- length(x)
+	maxy <- c(max(x), max(y))	#Set initial values for parameters
+	lambda1 <- lambda[1]
+	lambda2 <- lambda[2]
+	lambda3 <- lambda[3]
+	if((x == 0) | (y == 0)) {
+		prob <- matrix(NA, nrow = maxy[1] + 1, ncol = maxy[2]+1, byrow = T)
+		prob[maxy[1] + 1, maxy[2] + 1] <- exp( - lambda3) * 
+			dpois(x[j], lambda1[j]) * dpois(y[j], lambda2[j])
+	}
+	else {
+		prob <- matrix(NA, nrow = maxy[1] + 1, ncol = maxy[2]+1, byrow = T)
+		k <- 1
+		m <- 1
+		prob[k, m] <- exp( - lambda1 - lambda2 - lambda3)
+		for(i in 2:(maxy[1] + 1)) {
+			prob[i, 1] <- (prob[i - 1, 1] * lambda1)/(i - 1)
+		}
+		for(j in 2:(maxy[2] + 1)) {
+			prob[1, j] <- (prob[1, j - 1] * lambda2)/(j - 1)
+		}
+		for(j in 2:(maxy[2] + 1)) {
+			for(i in 2:(maxy[1] + 1)) {
+				prob[i, j] <- (lambda1 * prob[i - 1, j] + 
+				  lambda3 * prob[i - 1, j - 1])/(i - 1)
+			}
+		}
+	}
+	result <- prob
+	result
+}
+