Fixes to some CRAN check complaints.

references #542

R/InitErgmProposal.R

@@ -197,7 +197,7 @@ InitErgmProposal.BDStratTNT <- function(arguments, nw) {
 #' @templateVar name CondDegree
 #' @aliases InitErgmProposal.CondDegree
 #' @title MHp for degree constraints
-#' @description MHp for \eqn{constraints= ~degree}. Propose either 4 toggles (MH_CondDegreeTetrad) or 6 toggles
+#' @description MHp for `constraints= ~degree`. Propose either 4 toggles (MH_CondDegreeTetrad) or 6 toggles
 #'   (MH_CondDegreeHexad) at once. For undirected networks, propose 4 toggles (MH_CondDegreeTetrad).
 #'   MH_CondDegreeTetrad selects two edges with no nodes in common, A1-A2 and B1-B2, s.t. A1-B2 and B1-A2 are
 #'   not edges, and propose to replace the former two by the latter two. MH_CondDegreeHexad selects three edges
@@ -212,7 +212,7 @@ InitErgmProposal.CondDegree <- function(arguments, nw) {
 #' @templateVar name CondDegreeMix
 #' @aliases InitErgmProposal.CondDegreeMix
 #' @title MHp for degree mix constraints
-#' @description MHp for \eqn{constraints= ~degreesmix}. Similar to `InitErgmProposal.CondDegree`, except that
+#' @description MHp for `constraints= ~degreesmix`. Similar to `InitErgmProposal.CondDegree`, except that
 #'   the toggle is proposed only if the mixing matrix of degrees is preserved before and after the toggle.
 #' @template ergmProposal-general
 NULL
@@ -225,7 +225,7 @@ InitErgmProposal.CondDegreeMix <- function(arguments, nw) {
 #' @templateVar name CondOutDegree
 #' @aliases InitErgmProposal.CondOutDegree
 #' @title MHp for odegree constraints
-#' @description MHp for \eqn{constraints= ~odegrees}. For directed networks, randomly select two dyads with a
+#' @description MHp for `constraints= ~odegrees`. For directed networks, randomly select two dyads with a
 #'   common tail node, one having an edge and one not, and propose to swap the tie from one head to the other.
 #' @template ergmProposal-general
 NULL
@@ -240,7 +240,7 @@ InitErgmProposal.CondOutDegree <- function(arguments, nw) {
 #' @templateVar name CondInDegree
 #' @aliases InitErgmProposal.CondInDegree
 #' @title MHp for idegree constraints
-#' @description MHp for \eqn{constraints= ~idegrees}. For directed networks, randomly select two dyads with a
+#' @description MHp for `constraints= ~idegrees`. For directed networks, randomly select two dyads with a
 #'   common head node, one having an edge one not, and propose to swap the tie from one tail to the other.
 #' @template ergmProposal-general
 NULL
@@ -255,8 +255,8 @@ InitErgmProposal.CondInDegree <- function(arguments, nw) {
 #' @templateVar name CondB1Degree
 #' @aliases InitErgmProposal.CondB1Degree
 #' @title MHp for b1degree constraints
-#' @description MHp for \eqn{constraints= ~b1degrees}. For bipartite networks, randomly select an edge {B1i, B2j}
-#'   and an empty dyad with the same node B1i, {B1i, B2k}, and propose to toggle both {B1i, B2j} and {B1i, B2k}.
+#' @description MHp for `constraints= ~b1degrees`. For bipartite networks, randomly select an edge (B1i, B2j)
+#'   and an empty dyad with the same node B1i, (B1i, B2k), and propose to toggle both (B1i, B2j) and (B1i, B2k).
 #'   This ensures that the degrees of individual nodes in mode 1 are preserved.
 #' @template ergmProposal-general
 NULL
@@ -271,8 +271,8 @@ InitErgmProposal.CondB1Degree <- function(arguments, nw) {
 #' @templateVar name CondB2Degree
 #' @aliases InitErgmProposal.CondB2Degree
 #' @title MHp for b2degree constraints
-#' @description MHp for \eqn{constraints= ~b2degrees}. For bipartite networks, randomly select an edge {B1j, B2i}
-#'   and an empty dyad with the same node B2i, {B1k, B2i}, and propose to toggle both {B1j, B2i} and {B1k, B2i}.
+#' @description MHp for `constraints= ~b2degrees`. For bipartite networks, randomly select an edge (B1j, B2i)
+#'   and an empty dyad with the same node B2i, (B1k, B2i), and propose to toggle both (B1j, B2i) and (B1k, B2i).
 #'   This ensures that the degrees of individual nodes in mode 2 are preserved.
 #' @template ergmProposal-general
 NULL
@@ -286,7 +286,7 @@ InitErgmProposal.CondB2Degree <- function(arguments, nw) {
 #' @templateVar name CondDegreeDist
 #' @aliases InitErgmProposal.CondDegreeDist
 #' @title MHp for degreedist constraints
-#' @description MHp for \eqn{constraints= ~degreedist}. Randomly select a node (T) and its edge (E).  If the head
+#' @description MHp for `constraints= ~degreedist`. Randomly select a node (T) and its edge (E).  If the head
 #'   node of the edge (H) has 1 degree more than another randomly select node (A), and A is disconnected to both
 #'   T and H, then propose to toggle E and the dyad between T and A.
 #' @template ergmProposal-general
@@ -307,7 +307,7 @@ InitErgmProposal.CondDegreeDist <- function(arguments, nw) {
 #' @templateVar name CondInDegreeDist
 #' @aliases InitErgmProposal.CondInDegreeDist
 #' @title MHp for idegreedist constraints
-#' @description MHp for \eqn{constraints= ~idegreedist}. For directed networks, similar to
+#' @description MHp for `constraints= ~idegreedist`. For directed networks, similar to
 #'   `InitErgmProposal.CondDegreeDist`, except for indegree case
 #' @template ergmProposal-general
 NULL
@@ -327,7 +327,7 @@ InitErgmProposal.CondInDegreeDist <- function(arguments, nw) {
 #' @templateVar name CondOutDegreeDist
 #' @aliases InitErgmProposal.CondOutDegreeDist
 #' @title MHp for odegreedist constraints
-#' @description MHp for \eqn{constraints= ~odegreedist}. For directed networks, similar to
+#' @description MHp for `constraints= ~odegreedist`. For directed networks, similar to
 #'   `InitErgmProposal.CondDegreeDist`, except for outdegree case
 #' @template ergmProposal-general
 NULL
@@ -348,11 +348,12 @@ InitErgmProposal.CondOutDegreeDist <- function(arguments, nw) {
 #' @templateVar name ConstantEdges
 #' @aliases InitErgmProposal.ConstantEdges
 #' @title MHp for edges constraints
-#' @description MHp for \eqn{constraints= ~edges}. Propose pairs of toggles that keep number of edges the same.
+#' @description MHp for `constraints= ~edges`. Propose pairs of toggles that keep number of edges the same.
 #'   This is done by:
-#'   a. choosing an existing edge at random;
-#'   b. choosing a dyad at random that does not have an edge; and
-#'   c. proposing toggling both these dyads.
+#'
+#'   1. choosing an existing edge at random;
+#'   2. choosing a dyad at random that does not have an edge; and
+#'   3. proposing toggling both these dyads.
 #' @template ergmProposal-general
 NULL
 InitErgmProposal.ConstantEdges <- function(nw, arguments, ...) {

R/InitErgmTerm.R

@@ -906,7 +906,7 @@ InitErgmTerm.b1degrange<-function(nw, arglist, ..., version=packageVersion("ergm
 #' @templateVar name b1cov
 #' @title Main effect of a covariate for the first mode in a bipartite network
 #' @description This term adds a single network statistic for each quantitative attribute or matrix column to the model equaling the total
-#'   value of `attr(i)` for all edges /eqn{(i,j)} in the network. This
+#'   value of `attr(i)` for all edges \eqn{(i,j)} in the network. This
 #'   term may only be used with bipartite networks. For categorical attributes,
 #'   see `b1factor` .
 #'   

R/ergm-defunct.R

@@ -10,7 +10,6 @@
 # The last home for functions to removed from ergm.
 
 #' @name ergm-defunct
-#' @usage sociality(object, ...)
 #' @title Functions that have been removed from this package
 #' @description Functions that have been removed after a period of deprecation.
 #' @param ... Arguments to defunct functions.

R/ergm.R

@@ -299,7 +299,7 @@
 #' \emph{Journal of Statistical Software}, 24(3).
 #' \doi{10.18637/jss.v024.i03}
 #'
-#' Karwa V, Krivitsky PN, and Slavkovi\'{c} AB (2017). Sharing Social Network
+#' Karwa V, Krivitsky PN, and Slavkovi\'c AB (2017). Sharing Social Network
 #' Data: Differentially Private Estimation of Exponential-Family Random
 #' Graph Models. \emph{Journal of the Royal Statistical Society, Series
 #' C}, 66(3):481--500. \doi{10.1111/rssc.12185}

R/ergm_model.R

@@ -139,7 +139,7 @@ ergm_model <- function(formula, nw=NULL, silent=FALSE, ..., term.options=list(),
 #' term with a specifies name, calls it with the specified arguments,
 #' and returns the result.
 #'
-#' @param A term from an [ergm()] formula: typically a [`name`] or a
+#' @param term A term from an [ergm()] formula: typically a [`name`] or a
 #'   [`call`].
 #' @param env Environment in which it is to be evaluated.
 #' @param nw A [`network`] object.

R/ergm_state.R

@@ -14,7 +14,6 @@
 #' used to start another MCMC sampler. It is deliberately loosely
 #' specified, and its structure and even name are subject to change.
 #'
-#' @param nw a [`network`] object.
 #' @param nw0 a [`network`] object, whose edges are absent or ignored.
 #' @param model an [`ergm_model`] object.
 #' @param ext.state a list equal to the number of terms in the model,

R/get.node.attr.R

@@ -279,7 +279,7 @@ NULL
 #'   frame output. See the Details section for the specification.
 #' @param accept A character vector listing permitted data types for
 #'   the output. See the Details section for the specification.
-#' @param l,a arguments to `LARGEST`, which is actually a function
+#' @param a arguments to `LARGEST`, which is actually a function
 #'   that gets processed as a function level spec does.
 #' @param ... Additional argument to the functions of network or to
 #'   the formula's environment.

R/summary.ergm_model.R

@@ -18,7 +18,6 @@
 #' @param nw a [`network`] whose statistics are to be evaluated,
 #'   though an [`ergm_state`] object will also work. If `NULL`,
 #'   returns empty network's statistics for that model.
-#' @template response
 #' @template dotdotdot
 #' 
 #' @seealso [summary_formula()]

src/wtedgetree.c

@@ -285,7 +285,7 @@ void Wtprintedge(Edge e, WtTreeNode *edges){
   Rprintf("\t.parent=%d\n",edges[e].parent);
   Rprintf("\t.left=%d\n",edges[e].left);
   Rprintf("\t.right=%d\n",edges[e].right);
-  Rprintf("\t.weight=%d\n",edges[e].weight);
+  Rprintf("\t.weight=%f\n",edges[e].weight);
 }
 
 /*****************