rmove: Generate random moves on a fiber

In dkahle/algstat: Algebraic Statistics

Generate random moves on a fiber

Description

Generate random moves on a fiber

Usage

rmove(
  n,
  A,
  b,
  x,
  method = c("sis", "walk", "hybrid"),
  dist = c("uniform", "hypergeometric"),
  parallel = FALSE,
  format = c("mat", "vec", "tab"),
  dim,
  ...
)

Arguments

n	the number of observations
A	the configuration matrix of the model defining the fiber
b	integer vector; the vector of sufficient statistics
x	integer vector; a vector in the fiber to be used as an initialization point for the "walk" method
method	"sis", "walk", or "hybrid"
dist	"uniform" or "hypergeometric"
parallel	parallelize the sampling?
format	format of the returned moves, "mat", "vec", or "tab"
dim	the dimensions of the table if "tab" is used, see vec2tab()
...	arguments to pass to rfiber(), such as parallel = TRUE

Value

a named numeric vector

Author(s)

David Kahle [e-mail], Ruriko Yoshida [e-mail]

See Also

rfiber()

Examples

data(politics); politics
(x <- tab2vec(politics))

(A <- hmat(c(2,2), 1:2)) # independence model on 2x2 table
(b <- A %*% x) # vector of sufficient statistics
rmove(10, A = A, b = b)

## Not run:  # requires 4ti2

rmove(10, A = A, x = x, method = "walk")




moves <- rmove(10000, A = A, x = x, method = "walk")
unique(t(moves))


## simple example
(A <- hmat(c(2,2), 1:2))
(x <- c(1, 3, 3, 1))
(b <- rep.int(4, 4))

rfiber(10, A = A, b = b)
(tabs <- rfiber(10, A = A, b = b, format = "vec"))
unique(tabs)
lapply(unique(tabs), vec2tab, dim = c(2, 2))



library(microbenchmark)
microbenchmark(
  rmove(100, A = A, b = b),
  rmove(100, A = A, x = x, method = "walk")
)



markov(A)
markov(A, "vec")
markov(A, "tab", c(2,2))

rmove(5, A, b)
rmove(5, A, b, format = "vec")
rmove(5, A, b, format = "tab", dim = c(2,2))




## politics example
data(politics); politics
tab2vec(politics)
(b <- A %*% tab2vec(politics))
(tabs <- rfiber(1000, A = A, b = b, format = "vec"))
lapply(unique(tabs), vec2tab, dim = c(2, 2))

rmove(5, A, b)
rmove(5, A, b, format = "tab", dim = c(2,2))



## parallelizing
system.time(rmove(1e4, A, b))                  # ~35s
system.time(rmove(1e4, A, b, parallel = TRUE)) # ~ 8s, 8 cores










## drugs example
data(drugs)
(A <- hmat(c(2,2,2), 1:3))
(b <- A %*% tab2vec(drugs))
markovMoves <- markov(A)
rmove(5, A, b)
rmove(5, A, b, format = "tab", dim = c(2,2,2))




## End(Not run)

dkahle/algstat documentation built on May 23, 2023, 12:29 a.m.