Epidemiological metrics for netdiffuseR

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: netdiffuseR
 Title: Analysis of Diffusion and Contagion Processes on Networks
-Version: 1.25.0
+Version: 1.26.0
 Authors@R: c(
   person("George", "Vega Yon", email="g.vegayon@gmail.com", role=c("aut", "cre"),
     comment=c(ORCID = "0000-0002-3171-0844", what="Rewrite functions with Rcpp, plus new features")
@@ -57,11 +57,13 @@ URL: https://github.com/USCCANA/netdiffuseR,
  https://USCCANA.github.io/netdiffuseR/
 BugReports: https://github.com/USCCANA/netdiffuseR/issues
 Classification/MSC: 90C35, 90B18, 91D30
-Collate: 
+Collate:
     'RcppExports.R'
     'imports.r'
     'graph_data.r'
     'adjmat.r'
+    'adoption_mechanisms.R'
+    'disadoption_mechanisms.R'
     'bass.r'
     'bootnet.r'
     'citer_environment.R'
@@ -70,8 +72,10 @@ Collate:
     'degree_adoption_diagnostic.R'
     'diffnet-c.R'
     'diffnet-class.r'
+    'diffnet-epi.R'
     'diffnet-indexing.r'
     'diffnet-methods.r'
+    'epi_metrics.R'
     'egonets.R'
     'formula.r'
     'igraph.r'
@@ -89,8 +93,11 @@ Collate:
     'rdiffnet.r'
     'read_write_foreign.r'
     'select_egoalter.R'
+    'source_attribution.R'
     'spatial.R'
     'stats.R'
+    'status_accessors.R'
     'struct_equiv.R'
     'struct_test.R'
     'survey_to_diffnet.R'
+    'transmission.R'

NAMESPACE

@@ -40,6 +40,8 @@ S3method(dimnames,diffnet)
 S3method(fitbass,default)
 S3method(fitbass,diffnet)
 S3method(ftable,diffnet_adopters)
+S3method(generation_time,default)
+S3method(generation_time,diffnet_epi)
 S3method(hist,diffnet_bootnet)
 S3method(hist,diffnet_struct_test)
 S3method(image,diffnet_diffmap)
@@ -51,6 +53,8 @@ S3method(is_undirected,default)
 S3method(is_undirected,diffnet)
 S3method(is_valued,default)
 S3method(is_valued,diffnet)
+S3method(peak_prevalence,diffnet)
+S3method(peak_time,diffnet)
 S3method(plot,diffnet)
 S3method(plot,diffnet_adopters)
 S3method(plot,diffnet_bass)
@@ -59,6 +63,7 @@ S3method(plot,diffnet_degSeq)
 S3method(plot,diffnet_diffmap)
 S3method(plot,diffnet_hr)
 S3method(plot,diffnet_mentor)
+S3method(plot,netdiffuseR_repr)
 S3method(plot_diffnet,default)
 S3method(plot_diffnet,diffnet)
 S3method(plot_diffnet2,default)
@@ -70,27 +75,47 @@ S3method(print,degree_adoption_diagnostic)
 S3method(print,diffnet)
 S3method(print,diffnet_bootnet)
 S3method(print,diffnet_diffmap)
+S3method(print,diffnet_epi)
 S3method(print,diffnet_se)
 S3method(print,diffnet_struct_test)
+S3method(print,netdiffuseR_generation_time)
+S3method(print,netdiffuseR_repr)
+S3method(print,netdiffuseR_sar)
+S3method(print,netdiffuseR_survival)
 S3method(recode,data.frame)
 S3method(recode,matrix)
+S3method(repr_number,default)
+S3method(repr_number,diffnet_epi)
+S3method(secondary_attack_rate,default)
+S3method(secondary_attack_rate,diffnet_epi)
 S3method(str,diffnet)
 S3method(summary,diffnet)
 S3method(summary,diffnet_adoptChanges)
+S3method(summary,diffnet_epi)
+S3method(survival_curve,diffnet)
 S3method(t,diffnet)
+S3method(toa,diffnet)
+S3method(toa_all,diffnet)
+S3method(tod,diffnet)
+S3method(tod_all,diffnet)
 S3method(transformGraphBy,dgCMatrix)
 S3method(transformGraphBy,diffnet)
 export("%*%")
 export("diffnet.attrs<-")
 export("diffnet.toa<-")
 export(adjmat_to_edgelist)
 export(adopt_changes)
+export(adoptmech_logit)
+export(adoptmech_probit)
+export(adoptmech_threshold)
 export(approx_geodesic)
 export(approx_geodist)
 export(as.dgCMatrix)
 export(as_dgCMatrix)
 export(as_diffnet)
+export(as_diffnet_epi)
 export(as_spmat)
+export(as_transmission_tree)
 export(bass_F)
 export(bass_dF)
 export(bass_f)
@@ -114,6 +139,10 @@ export(diffnet_to_network)
 export(diffnet_to_networkDynamic)
 export(diffreg)
 export(diffusionMap)
+export(disadoptmech_bithreshold)
+export(disadoptmech_logit)
+export(disadoptmech_probit)
+export(disadoptmech_random)
 export(drawColorKey)
 export(drop_isolated)
 export(edgelist_to_adjmat)
@@ -123,12 +152,14 @@ export(ego_variance)
 export(egonet_attrs)
 export(exposure)
 export(fitbass)
+export(generation_time)
 export(graph_power)
 export(grid_distribution)
 export(hazard_rate)
 export(igraph_to_diffnet)
 export(igraph_vertex_rescale)
 export(infection)
+export(is.diffnet_epi)
 export(is_multiple)
 export(is_self)
 export(is_undirected)
@@ -150,6 +181,8 @@ export(nnodes)
 export(nodes)
 export(nslices)
 export(nvertices)
+export(peak_prevalence)
+export(peak_time)
 export(permute_graph)
 export(plot_adopters)
 export(plot_diffnet)
@@ -165,6 +198,7 @@ export(read_pajek)
 export(read_ucinet)
 export(read_ucinet_head)
 export(recode)
+export(repr_number)
 export(resample_graph)
 export(rescale_vertex_igraph)
 export(rewire_graph)
@@ -175,17 +209,28 @@ export(rgraph_er)
 export(rgraph_ws)
 export(ring_lattice)
 export(round_to_seq)
+export(secondary_attack_rate)
 export(select_egoalter)
+export(source_attribution_earliest)
+export(source_attribution_uniform)
+export(source_attribution_weighted)
 export(split_behaviors)
 export(struct_equiv)
 export(struct_test)
 export(struct_test_asymp)
 export(survey_to_diffnet)
+export(survival_curve)
 export(susceptibility)
 export(threshold)
+export(toa)
+export(toa_all)
 export(toa_diff)
 export(toa_mat)
+export(tod)
+export(tod_all)
 export(transformGraphBy)
+export(transmission_tree)
+export(transmission_tree_from_events)
 export(vertex_covariate_compare)
 export(vertex_covariate_dist)
 export(vertex_mahalanobis_dist)

NEWS.md

@@ -11,6 +11,9 @@
 * New dataset `epigames` and `epigamesDiffNet`: a simulated epidemic game
   network with 594 nodes and 15 time periods from the WKU Epi Games study.
 
+* `exposure()` and `rdiffnet()` now support `mode = "stochastic"`, allowing
+  for probabilistic interpretation of edge weights in exposure calculations.
+
 ## Internal changes
 
 * Fixed CRAN example error in `round_to_seq()`: `plot(w, x)` replaced with
@@ -19,7 +22,6 @@
 
 * Removed `configure` framework. R already provides paths and configuration for OpenMP.
 
-
 # Changes in netdiffuseR version 1.24.0 (2025-12-09)
 
 * New function `degree_adoption_diagnostic()` analyzes the correlation between network 

R/adjmat.r

@@ -537,6 +537,109 @@ toa_mat.default <- function(per, t0, t1) {
   )
 }
 
+# Status-array helpers.
+#
+# A -status- array carries the multi-cycle state of a diffnet: 1 wherever
+# node i is adopted at time t for behaviour q, 0 otherwise. It need not be
+# monotone (adoption + recovery cycles, behavioural relapse, etc.).
+#
+# Single-behaviour layout: an n x T integer matrix.
+# Multi-behaviour  layout: a length-Q list of n x T integer matrices.
+#
+# These helpers mirror -toa_mat- (which builds the absorbing case from -toa-)
+# but consume -status- directly.
+
+# Internal: build {adopt, cumadopt} matrices from a single-behaviour status.
+# - cumadopt is exactly status (alias; no copy thanks to R's COW).
+# - adopt[i, t] = 1 iff status[i, t] == 1 AND (t == 1 OR status[i, t-1] == 0).
+#   That is, every "fresh" entry into the adopted state.
+status_mat_single <- function(status, t0, t1, labels = NULL) {
+  storage.mode(status) <- "integer"
+  n <- nrow(status)
+  T <- ncol(status)
+
+  cumadopt <- status
+  adopt    <- matrix(0L, n, T)
+  if (T >= 1L) adopt[, 1L] <- cumadopt[, 1L]
+  if (T >= 2L) {
+    prev  <- cumadopt[, 1:(T - 1L), drop = FALSE]
+    curr  <- cumadopt[, 2:T,        drop = FALSE]
+    fresh <- (curr == 1L) & (prev == 0L)
+    sub   <- adopt[, 2:T, drop = FALSE]
+    sub[fresh] <- 1L
+    adopt[, 2:T] <- sub
+  }
+
+  rn <- if (length(labels)) labels else seq_len(n)
+  dimnames(adopt)    <- list(rn, t0:t1)
+  dimnames(cumadopt) <- list(rn, t0:t1)
+  list(adopt = adopt, cumadopt = cumadopt)
+}
+
+# Public-facing dispatcher: returns the same shape as -toa_mat-.
+status_mat <- function(status, t0, t1, labels = NULL) {
+  if (is.list(status)) {
+    lapply(status, status_mat_single, t0 = t0, t1 = t1, labels = labels)
+  } else {
+    status_mat_single(status, t0 = t0, t1 = t1, labels = labels)
+  }
+}
+
+# Derive -toa- from a status array: first time of 1 per node (per behaviour).
+# Returns an integer vector for single-behaviour, an n x Q matrix otherwise.
+# Names / rownames are intentionally NOT preserved — -new_diffnet- assigns
+# them from -meta$ids- downstream so the diffnet's labelling stays canonical.
+toa_from_status <- function(status, t0 = 1L) {
+  if (is.list(status)) {
+    Q <- length(status)
+    n <- nrow(status[[1L]])
+    out <- matrix(NA_integer_, n, Q)
+    for (q in seq_len(Q)) out[, q] <- toa_from_status(status[[q]], t0 = t0)
+    return(out)
+  }
+
+  n <- nrow(status)
+  vapply(seq_len(n), function(i) {
+    idx <- which(status[i, ] == 1L)
+    if (length(idx)) as.integer(idx[1L] + t0 - 1L) else NA_integer_
+  }, integer(1L))
+}
+
+# Validation for -status- supplied to -new_diffnet-.
+validate_status <- function(status, n, num_of_behaviors) {
+  if (num_of_behaviors == 1L) {
+    if (!is.matrix(status))
+      stop("-status- for a single-behaviour diffnet must be an n x T matrix.")
+    if (nrow(status) != n)
+      stop("-status- has ", nrow(status), " rows but the graph has ", n,
+           " nodes.")
+    if (any(!status %in% c(0L, 1L, NA_integer_, 0, 1)))
+      stop("-status- entries must be 0 or 1.")
+  } else {
+    if (!is.list(status))
+      stop("-status- for a multi-behaviour diffnet must be a length-Q list ",
+           "of n x T matrices.")
+    if (length(status) != num_of_behaviors)
+      stop("-status- has length ", length(status),
+           " but -toa- carries ", num_of_behaviors, " behaviours.")
+    for (q in seq_along(status)) {
+      if (!is.matrix(status[[q]]))
+        stop("-status[[", q, "]]- must be an n x T matrix.")
+      if (nrow(status[[q]]) != n)
+        stop("-status[[", q, "]]- has ", nrow(status[[q]]),
+             " rows but the graph has ", n, " nodes.")
+      if (any(!status[[q]] %in% c(0L, 1L, NA_integer_, 0, 1)))
+        stop("-status[[", q, "]]- entries must be 0 or 1.")
+    }
+    # All behaviours must share a common T.
+    Ts <- vapply(status, ncol, integer(1L))
+    if (length(unique(Ts)) > 1L)
+      stop("All entries of -status- must share the same number of columns ",
+           "(time periods).")
+  }
+  invisible(TRUE)
+}
+
 # @rdname toa_mat
 # @export
 toa_mat.numeric <- function(times, labels=NULL,