?bugs
?summary
heisenberg <- read.csv(file="/Users/rrtucci/Desktop/R-lessons/kellyBlackRTutorial/simple.cvs",head=TRUE,sep=",")
heisenberg
summary()
summary(heisenberg)
heisenberg$trial
heis$trial
heis
tree <- read.csv(file="/Users/rrtucci/Desktop/R-lessons/kellyBlackRTutorial/trees91.csv",header=TRUE,sep=",")
attributes(heisenberg)
help(read)
ls()
tree$C
x <- seq(-20,20,by=.1)
x
y <- dnorm(x) ;plot(x,y)
y<-probit(x);plot(x,y)
help(probit)
y=pnorm(x); plot(x,y)
help(logit)
y=log(x/(1-x));plot(x,y)
x=seq(-2000,2000,by=100); plot(x,y)
y
x
y=log(x/(1-x))
y
x=seq(0,1,.05);
y=log(x/(1-x))
y
plot(x,y)
stripchart(tree$N)
stripchart(tree$C)
stripchart(x)
stipchart(tree$C, method="stack")
stripchart(tree$C, method="stack")
stripchart(tree$C, method="jitter")
title('Leaf BioMass in High CO2 Environment',xlab='BioMass of Leaves')
hist(tree$C)
tree$C
hist(tree$C, xlim(0,4))
 hist(tree$C, xlim=c(0,4))
boxplot(heisenberg$mass)
plot(tree$STBM,tree$LFBM)
?plot
a=c(2,3)
a=c(2,3)
b=3
a=c(2,3)#
b=3
data = list(#
	p_A = structure(.Data = c(#
		0.3,	0.1,	0.75,	0.5,	0.5,	0.5,	0.5,	0.5,	#
		0.7,	0.9,	0.25,	0.5,	0.5,	0.5,	0.5,	0.5#
	), .Dim = c(2,8)),#
	p_B = structure(.Data = c(#
		0.5,	0.5,	0.5,	0.5,	#
		0.5,	0.5,	0.5,	0.5#
	), .Dim = c(2,4)),#
	p_C = structure(.Data = c(#
		0.8,	0.5,	#
		0.2,	0.5#
	), .Dim = c(2,2)),#
	p_D = c(#
		0.4,	#
		0.6#
	)#
)
p_A
data$p_A
data = list(#
	p_A = structure(.Data = c(#
		0.3,	0.1,	0.75,	0.5,	0.5,	0.5,	0.5,	0.5,	#
		0.7,	0.9,	0.25,	0.5,	0.5,	0.5,	0.5,	0.5#
	), .Dim = c(8,2)),#
	p_B = structure(.Data = c(#
		0.5,	0.5,	0.5,	0.5,	#
		0.5,	0.5,	0.5,	0.5#
	), .Dim = c(4,2)),#
	p_C = structure(.Data = c(#
		0.8,	0.5,	#
		0.2,	0.5#
	), .Dim = c(2,2)),#
	p_D = c(#
		0.4,	#
		0.6#
	)#
)
data$p_A
summary(data)
plot(data)
print(data)
getwd()
load("R2WinBUGS")#
#
#define distributions of categorical nodes#
#varying in-states first#
data = list(#
	p_A = structure(.Data = c(#
		0.3,	0.1,	0.75,	0.5,	0.5,	0.5,	0.5,	0.5,	#
		0.7,	0.9,	0.25,	0.5,	0.5,	0.5,	0.5,	0.5#
	), .Dim = c(8,2)),#
	p_B = structure(.Data = c(#
		0.5,	0.5,	0.5,	0.5,	#
		0.5,	0.5,	0.5,	0.5#
	), .Dim = c(4,2)),#
	p_C = structure(.Data = c(#
		0.8,	0.5,	#
		0.2,	0.5#
	), .Dim = c(2,2)),#
	p_D = c(#
		0.4,	#
		0.6#
	)#
)#
#
parameters = list(#
	"A",#
	"B",#
	"C",#
	"D"#
)#
#
#random inits#
#runif = random uniform (num samples, min, max)#
inits = function() list(#
	A = 1 + trunc(runif(1, 0, 2),#
	B = 1 + trunc(runif(1, 0, 2),#
	C = 1 + trunc(runif(1, 0, 2),#
	D = 1 + trunc(runif(1, 0, 2)#
)
inits
summary(inits)
4nodeFullyConnected_sim = bugs(#
	data, inits, parameters,#
	"4nodeFullyConnected_BUGS.txt",#
	n.chains=3,#
	n.iter=1000,#
	DIC=FALSE)  #no nodes are observed so DIC is undefined#
print(4nodeFullyConnected_sim)#
plot(4nodeFullyConnected_sim)
4nodeFullyConnected_sim = bugs(#
	data, inits, parameters,#
	"4nodeFullyConnected_BUGS.txt",#
	n.chains=3,#
	n.iter=1000,#
	DIC=FALSE)  #no nodes are observed so DIC is undefined#
print(4nodeFullyConnected_sim)#
plot(4nodeFullyConnected_sim)
?bugs
??bugs
inits(1)
#random inits#
#runif = random uniform (num samples, min, max)#
inits = function() list(#
	A = 1 + trunc(runif(1, 0, 2),#
	B = 1 + trunc(runif(1, 0, 2),#
	C = 1 + trunc(runif(1, 0, 2),#
	D = 1 + trunc(runif(1, 0, 2)#
)#
#
4nodeFullyConnected_sim = bugs(#
	data, inits, parameters,#
	"4nodeFullyConnected_BUGS.txt",#
	n.chains=3,#
	n.iter=1000,#
	DIC=FALSE)  #no nodes are observed so DIC is undefined#
print(4nodeFullyConnected_sim)#
plot(4nodeFullyConnected_sim)
#random inits#
#runif = random uniform (num samples, min, max)#
inits = function() list(#
	A = 1 + trunc(runif(1, 0, 2),#
	B = 1 + trunc(runif(1, 0, 2),#
	C = 1 + trunc(runif(1, 0, 2),#
	D = 1 + trunc(runif(1, 0, 2)#
)
parameters = list(#
	"A",#
	"B",#
	"C",#
	"D"#
)
parameters = list(#
	"A",#
	"B",#
	"C",#
	"D"#
)
#random inits#
#runif = random uniform (num samples, min, max)#
inits = function() list(#
	A = 1 + trunc(runif(1, 0, 2)),#
	B = 1 + trunc(runif(1, 0, 2)),#
	C = 1 + trunc(runif(1, 0, 2)),#
	D = 1 + trunc(runif(1, 0, 2))#
)
inits
inits()
inits()
inits()
inits()
4nodeFullyConnected_sim = bugs(#
	data, inits, parameters,#
	"4nodeFullyConnected_BUGS.txt",#
	n.chains=3,#
	n.iter=1000,#
	DIC=FALSE)  #no nodes are observed so DIC is undefined#
print(4nodeFullyConnected_sim)#
plot(4nodeFullyConnected_sim)
4nodeFullyConnected_sim = bugs(data, inits, parameters,"4nodeFullyConnected_BUGS.txt",n.chains=3,n.iter=1000,DIC=FALSE)
