function to calculate network statistics for an arbitrary raw socioma…

…trix

NAMESPACE

@@ -3,6 +3,7 @@
 export(Estimate_Plot)
 export(GOF)
 export(Trace_Plot)
+export(calculate_network_statistics)
 export(find_example_simulated_network)
 export(gergm)
 export(hysteresis)

R/calculate_network_statistics.R

@@ -0,0 +1,67 @@
+#' @title A Function to estimate calculate (weighted) network statistics
+#' @description Calculates out2stars, in2stars, ctriads, mutual, ttriads, and
+#' edges statistics (with or without exponential downweighting) for a
+#' real-valued network.
+#'
+#' @param network A square numeric matrix (sociomatrix or adjacency matrix)
+#' representing the network.
+#' @param weights If you wish to provide your own weights, you must provide a
+#' vector of length 6 with terms corresponding to out2stars, in2stars, ctriads,
+#'mutual, ttriads, edges in that order.
+#' @param downweight_statistics_together Logical indicating whether exponential
+#' downweighting should be done together or separately. Defaults to TRUE.
+#' @return A gergm object containing parameter estimates.
+#' @export
+
+calculate_network_statistics <- function(
+  network,
+  weights = NULL,
+  downweight_statistics_together = TRUE) {
+
+
+  # hard coded possible stats
+  possible_stats <- c("out2stars",
+                      "in2stars",
+                      "ctriads",
+                      "mutual",
+                      "ttriads",
+                      "edges")
+
+  #if no weights are provided, make them all 1's
+  if (is.null(weights)){
+    weights <- rep(1, length(possible_stats))
+  } else if (length(weights) != length(possible_stats)) {
+    stop(paste("If you wish to provide your own weights, you must provide a vector of length",
+               length(possible_stats),"with terms corresponding to",
+               paste0(possible_stats,collapse = ", "), "in that order."))
+  }
+
+  # makre sure it is square
+  if (nrow(network) != ncol(network)) {
+    stop("The argument 'network' must be a square numeric matrix.")
+  }
+
+  # make sure the diagonal is zeros
+  diag(network) <- 0
+  # get the triples to pass in
+  num.nodes <- nrow(network)
+  triples <- t(combn(1:num.nodes, 3))
+
+  # calculate the statistics
+  statistics <- h2(network,
+                   triples = triples,
+                   statistics = rep(1, length(possible_stats)),
+                   alphas = weights,
+                   together = downweight_statistics_together)
+
+  #put everything in a data.frame
+  to_return <- data.frame(out2stars = statistics[1],
+                          in2stars  = statistics[2],
+                          ctriads = statistics[3],
+                          mutual = statistics[4],
+                          ttriads = statistics[5],
+                          edges = statistics[6],
+                          stringsAsFactors = FALSE)
+
+  return(to_return)
+}