convergence.check.value: Convergence check

In tbonne/netTS: netTS: network time series

Description

This function will estimate the convergence of the chosen network measure using random subsets of the data.

Usage

convergence.check.value(data, windowsize = days(30), windowshift = days(1),
  directed = FALSE, measureFun = strength, max.subsample.size = 30,
  SRI = FALSE, n.boot = 100, probs = c(0.025, 0.975))

Arguments

data	Dataframe with relational data in the first two rows, and a time stamp in the third row. Note: time stamps should be in ymd or ymd_hms format. The lubridate package can be very helpful in organizing times.
windowsize	The size of each window in which to generate a network.
windowshift	The amount of time to shift the window when generating networks.
directed	Whether to consider the network as directed or not (TRUE/FALSE).
measureFun	The function used to take network measurements.
max.subsample.size	The maximum number of samples to remove when recalculating the network metric.
SRI	Wether to use the simple ratio index or not (Default=FALSE).
n.boot	Number of times to repeate the subsample procedure (i.e., bootstrap estimate of slope)
probs	The probablility interval to calculate the confidence intervals.

tbonne/netTS documentation built on July 26, 2021, 2:27 a.m.