On Jul 10, 2011, at 9:09 PM, mousy0815 wrote:
I have the following code to determine the probability of a t-cell
encountering an antigen after "m" steps.
probability <- function(N, f, m, b, x, t) { #using ifelse instead of
if/else
#N is the number of lymph nodes
#f is the fraction of Dendritic cells (in the correct node) that
have the
antigen
#m is the number of time steps
#b is the starting position (somewhere in the node or somewhere in
the gap
between nodes. It is a number between 1 and (x+t))
#x is the number of time steps it takes to traverse the gap
#t is the number of time steps it takes to traverse a node.
A <- 1/N
B <- 1-A
C <- 1-f
D <- (((m+b-1)%%(x+t))+1)
ifelse(b<=t, ########starts inside node
ifelse( (m<=(t-b)),
return(B + A*(C^m)), # start & end in
first node
ifelse (D<=t, # we finish in a node
return((B + A*(C^(t-b)))*((B + A*(C^t))^(floor(m/(x
+t))-1))*(B +
A*(C^D))),
probability(N, f,
(m-1), b, x, t)
)
),
ifelse( ########starts outside node
m<=(x+t-b),
return(1), #also end in the gap,
ifelse (
(D<=t), #end in a node
(return(((B +
A*(C^t))^(floor((m/(x+t)))))*(B + (A*(C^D))))),
probability(N, f, (m-1), b, x,
t)#outside node
)
)
)
}
But I do:
m<- c(1:3)
probability(10, 0.1, m, 3, 4, 5)
0.9900000 0.9810000 0.9729000
but if you do each number separately you get
probability(10, 0.1, 1, 3, 4, 5)
0.99
probability(10, 0.1, 2, 3, 4, 5)
0.981
probability(10, 0.1, 3, 3, 4, 5)
0.981
Your function is probably not fully vectorized. Try comparing with
sapply(1:3, function(x) probability( m =x, N=0.1, f=3, b=3, x=4,
t=5) )
--
David.
Can someone tell me why this is happening??
--
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David Winsemius, MD
West Hartford, CT
______________________________________________
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