Import user data 2
import_user_STb2.RdFirst step of analysis pipeline: create STbayes data object from user supplied data to be used for generating and fitting models. This function is basically used when fitting models of complex transmission to high-resolution data. Rather than pre-process high res data, this will just create a massive data-list to be sent to Stan. Models created with this function will take much longer to run.
Usage
import_user_STb2(
event_data,
networks,
network_type = c("undirected", "directed"),
ILV_c = NULL,
ILV_tv = NULL,
ILVi = NULL,
ILVs = NULL,
ILVm = NULL,
t_weights = NULL,
high_res = FALSE
)Arguments
- event_data
dataframe with columns id, trial, time, t_end
- networks
Either a dataframe, a bisonr fit, or a list of bisonr fits. If dataframe: with columns trial, from, to, and one or more columns of edge weights named descriptively.
- network_type
"undirected" or "directed".
- ILV_c
optional dataframe with columns id, and any constant individual-level variables that might be of interest
- ILV_tv
optional dataframe with columns trial, id, time and any time-varying variables. Variable values should summarize the variable for each inter-acquisition period.
- ILVi
Optional character vector of column names from ILV metadata to be considered when estimating intrinsic rate. If not specified, all ILV are applied to both.
- ILVs
Optional character vector of column names from ILV metadata to be considered when estimating social transmission rate. If not specified, all ILV are applied to both.
- ILVm
Optional character vector of column names from ILV metadata to be considered in a multiplicative model.
- t_weights
Optional dataframe with columns trial, id, time and t_weight. Transmission rates represent rates of production/relevant cues per inter-event period.
- high_res
Boolean indicating whether or not user is providing networks and transmission weights per period duration=1