This vignette explains input arguments, output structure and usage of the function remify::rehshape()
.
remify::rehshape()
transforms a remify
object into another object with a structure that is suitable to external packages. The function can return the data inputs required by the functions:
relevent::rem()
relevent::rem.dyad()
Both functions are available inside the relevent package (Butts C., 2023).
The input arguments of remify::rehshape()
are:
data
, the processed relational event history (S3 object of class remify
)output_format
, a character value that indicates to which output format the input data
should be converted. This argument can assume two values: "relevent-rem"
, "relevent-rem.dyad"
(default is "relevent-rem"
)ncores
, number of threads used to parallelize internal routines (default is 1L
)optional_arguments
, vector of arguments names from relevent::rem
or relevent::rem.dyad()
that the user might want to process and have in the output object of rehshape (e.g., the pre-computed structures required by relevent::rem.dyad()
, such as acl
, cumideg
, etc.) - this feature will be available in a future version of remify -The output structure of the function is different according to the chosen output_format
:
output_format = "relevent-rem"
, then the output is an S3 object of class relevent-rem
, which contains: eventlist
, a matrix of two columns: observed dyads in the first column, vector of time in the second columnsupplist
, a logical matrix of dimensions [rows = number of events, columns = number of dyads]. The matrix indicates at each time point (by row) whether each dyad was at risk (TRUE
), or not (FALSE
)timing
, is a character that can assume two values: "interval"
(which uses the inter-event time in the model), or "ordinal"
(which only considers the event order in the model)
If output_format = "relevent-rem.dyad"
, then the output is an S3 object of class relevent-rem.dyad
, which contains:
edgelist
, a matrix of three columns: the time (or order) of the events in the first column, the sender and the receiver of the relational event, respectively, in the second and third columnn
, is the number of actors in the relational event network (senders and receivers)ordinal
, is a logical (TRUE
/FALSE
) value which indicates whether the likelihood should be 'ordinal' (TRUE
) or 'interval' (FALSE
)To explain the usage of the function remify::rehshape()
, we consider the example edgelist available with the data randomREH
. First, we process the edgelist with remify::remify()
.
library(remify) data(randomREH) reh_remify <- remify::remify(edgelist = randomREH$edgelist, model = "tie") reh_remify
Then, we can transform the remify
object to any of the possible output formats:
remify
to relevent-rem
:reh_rem <- remify::rehshape(data = reh_remify, output_format = c("relevent-rem")) names(reh_rem)
remify
to relevent-rem.dyad
:reh_rem.dyad <- remify::rehshape(data = reh_remify, output_format = c("relevent-rem.dyad")) names(reh_rem.dyad)
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