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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