rsextrobj {RaschSampler} | R Documentation |
Utility function to extract some of the generated matrices.
rsextrobj(RSobj, start = 1, end = 8192)
RSobj |
object as obtained from using rsampler |
start |
number of the matrix to start with. When specifying 1 (the default value) the original input matrix is included in the output object. |
end |
last matrix to be extracted. If end
is not specified, all matrices from RSobj
are extracted (the maximal value is 8192, see
rsctrl ). If end is larger than
the number of matrices stored in RSobj ,
end is set to the highest possible value
(i.e., n_tot ).
|
A list of class RSmpl
with components
n |
number of rows of the input matrix |
k |
number of columns of the input matrix |
inpmat |
the input matrix |
tfixed |
TRUE , if diagonals of inpmat are fixed |
burn_in |
length of the burn in process |
n_eff |
number of generated matrices (effective matrices) |
step |
controls the number number of void matrices generated in the the burn in
process and when effective matrices are generated (see note
in rsctrl ). |
seed |
starting value for the random number generator |
n_tot |
number of matrices in outvec . |
outvec |
vector of encoded random matrices |
ier |
error code |
By default, all generated matrices plus
the original matrix (in position 1) are contained in
outvec
, thus n_tot = n_eff + 1
. If
the original matrix is not in outvec
then
n_tot = n_eff
.
For saving and loading objects
of class RSobj
see the example below.
ctr <- rsctrl(burn_in = 10, n_eff = 3, step=10, seed = 0, tfixed = FALSE) mat <- matrix(sample(c(0,1), 50, replace = TRUE), nr = 10) all_m <- rsampler(mat, ctr) summary(all_m) some_m <- rsextrobj(all_m, 1, 2) summary(some_m) ## Not run: save(some_m, file = "some.RSobj") some_new <- load("some.RSobj") summary(some_new) ## End(Not run)