Develop

DESCRIPTION

@@ -2,8 +2,8 @@ Encoding: UTF-8
 Package: RSiena
 Type: Package
 Title: Siena - Simulation Investigation for Empirical Network Analysis
-Version: 1.6.10
-Date: 2026-06-14
+Version: 1.6.11
+Date: 2026-07-16
 Authors@R: c(person("Tom A.B.", "Snijders", role = c("aut", "ctb"), comment = c(ORCID = "0000-0003-3157-4157")),
               person("Ruth M.", "Ripley", role = "aut"),
               person("Krists", "Boitmanis", role = c( "aut","ctb")),

NAMESPACE

@@ -18,6 +18,7 @@ export(
    networkExtraction, behaviorExtraction,
 	OutdegreeDistribution, IndegreeDistribution, BehaviorDistribution,
 	TriadCensus, mixedTriadCensus, dyadicCov, egoAlterCombi, egoAlterCovarComb,
+   AC_Moran, AC_Geary,
 	siena_table, xtable, score.Test, Wald.RSiena, Multipar.RSiena, 
    testSame.RSiena, funnelPlot, meta.table,
 	influenceTable, selectionTable,
@@ -66,8 +67,10 @@ S3method(write_report, sienadata)
 S3method(print, sienaGroup)
 S3method(print, sienaDependent)
 S3method(print, sienaFit)
+S3method(print, coef_siena)
 S3method(summary, sienaFit)
 S3method(coef, sienaFit)
+S3method(coefficients, sienaFit)
 S3method(vcov, sienaFit)
 S3method(test_parameter, sienaFit)
 S3method(write_result, sienaFit)

NEWS.md

@@ -1,3 +1,21 @@
+2026-07-16
+
+# RSiena 1.6.11
+
+## Changes in RSiena:
+### Effects
+### Functionality
+  * New auxiliary functions `AC_Moran` and `AC_Geary`.
+  * In `transformScript`, the replacement for `sienaCompositionChangeFromFile`
+    was put before the replacement for `sienaCompositionChange`. 
+  * The component `theta` of results of function `siena`, the result of 
+    functions `coef`, and `estimate_onestep` have got a class `coef_siena`,
+    which has its own `print` method (to allow vertical printing).  
+  * Function `coef` now has default `shortenNames=FALSE`. 
+  * Alias `coefficients` for `coef`. 
+  * Remark to console about output file for `siena` only when
+    `silent=FALSE`. 
+
 2026-06-14
 
 # RSiena 1.6.10

R/TransformScript.R

@@ -73,8 +73,8 @@ namePairs <- list(c("sienaDependent", "as_dependent_rsiena"),
    c("sienaNet", "as_dependent_rsiena"),
    c("coCovar", "as_covariate_rsiena"),
    c("varDyadCovar", "as_covariate_rsiena"),
-   c("sienaCompositionChange", "as_composition_rsiena"),
    c("sienaCompositionChangeFromFile", "as_composition_file_rsiena"),
+   c("sienaCompositionChange", "as_composition_rsiena"),
    c("sienaNodeSet", "as_nodeset_rsiena"),
    c("sienaDataCreate", "make_data_rsiena"),
    c("sienaModelCreate", "sienaAlgorithmCreate"),

R/initializeFRAN.r

@@ -271,20 +271,23 @@ initializeFRAN <- function(z, x, data, effects, prevAns=NULL, initC,
 		{
 			if (!is.null(prevAns) && inherits(prevAns, "sienaFit"))
 			{
-				if (is.null(x$useOneStep))
+				if (is.null(x$useOneStep)) # undocumented feature; probably meaningless
 				{
 					x$useOneStep <- FALSE
 				}
 				if (x$useOneStep)
-				{
-					keepStill <- which(prevAns$fixed)
-					if (length(keepStill) == 0)
+				{	
+					if (is.null(x$keepStill))
+					{
+						x$keepStill <- which(prevAns$fixed)
+					}
+					if (length(x$keepStill) == 0)
 					{
-						keepStill <- 0
+						x$keepStill <- 0
 					}				
 				}
 				effects <- update_theta(effects, prevAns, 
-							onestep=x$useOneStep, keepUnchanged=keepStill)
+							onestep=x$useOneStep, keepUnchanged=x$keepStill)
 			}
 		}
 		## add any effects needed for settings model

R/phase3.r

@@ -167,7 +167,7 @@ phase3.2 <- function(z, x, ...)
         toosmall2 <- abs(sf) < 1e-10 * z$scale
         dmsf[toosmall] <- 1e-20 * z$scale[toosmall] * z$scale[toosmall]
         tstat <- rep(NA, z$pp)
-        tstat[!toosmall]<- sf[!toosmall] / sqrt(dmsf[!toosmall])
+        tstat[!toosmall] <- sf[!toosmall] / sqrt(dmsf[!toosmall])
         tstat[toosmall & toosmall2] <- 0
         tstat[toosmall & !toosmall2] <- NA
         z$tstat <- tstat

R/siena07.r

@@ -81,8 +81,11 @@ siena <- function(data = NULL, effects = NULL,
 				stop("For piped data, you need to give an outputName in the output control object.")
 			}				
 			control_out$outputName <- paste(dataName, "_out", sep="")
-			cat('siena will create/use an output file',
-				paste(control_out$outputName,'.txt',sep=''),'.\n')
+			if (!silent)
+			{
+				cat('siena will create/use an output file',
+					paste(control_out$outputName,'.txt',sep=''),'.\n')
+			}
 		}
 		control_out$projname <- control_out$outputName
 	}
@@ -256,7 +259,7 @@ siena <- function(data = NULL, effects = NULL,
 		## need to reset the random number type to the normal one
 		assign(".Random.seed", z$oldRandomNumbers, pos=1)
 	}
-
+	class(z$theta) <- "coef_siena"
 	class(z) <- "sienaFit"
 	attr(z, "version") <- packageDescription(pkgname, fields = "Version")
 	z$tkvars <- NULL
@@ -281,7 +284,8 @@ estimate_onestep <- function(x, fixed=x$fixed, r=1, shortenNames=FALSE)
 		bfixed <- (1:x$pp) %in% fixed
 	}
 	else # it should be logical
-	{	if (length(fixed) != x$pp)
+	{
+	if (length(fixed) != x$pp)
 		{
 			stop(paste('The length of the boolean vector is ', length(fixed),
 				', but it should be ', x$pp, '.', sep=''))		
@@ -292,6 +296,7 @@ estimate_onestep <- function(x, fixed=x$fixed, r=1, shortenNames=FALSE)
 	dfrac <- x$dfra[!bfixed, !bfixed]
 	meandev <- colMeans(x$sf[ , !bfixed])
 	onestep <- x$theta
+	dinv <- matrix(NA, x$pp, x$pp)
 # This will keep the bfixed parameter values
 	if (!all(bfixed))
 	{
@@ -307,6 +312,7 @@ estimate_onestep <- function(x, fixed=x$fixed, r=1, shortenNames=FALSE)
 	{
 		names(onestep) <- fromObjectToText(names(onestep))
 	}
+	class(onestep) <- "coef_siena"
 	onestep
 }
 
@@ -820,7 +826,7 @@ errorHandler <- function()
 }
 
 ##@coef.sienaFit method for sienaFit
-coef.sienaFit <- function(object, dropRates=TRUE, shortenNames=TRUE, ...)
+coef.sienaFit <- function(object, dropRates=TRUE, shortenNames=FALSE, ...)
 {
 	result <- object$theta
 	if (shortenNames)
@@ -833,16 +839,23 @@ coef.sienaFit <- function(object, dropRates=TRUE, shortenNames=TRUE, ...)
 	}	
 	if (dropRates)
 	{
-		return(result[!object$requestedEffects$basicRate])
-	}
-	else
-	{
-		return(result)
+		result <- result[!object$requestedEffects$basicRate]
 	}
+	class(result) <- "coef_siena"
+	result
 }
 
+
+coefficients <- function(object, ...) UseMethod("coefficients", object)
+
+coefficients.sienaFit <- function(object,  dropRates=TRUE, shortenNames=FALSE, ...)
+{   
+	coef(object, dropRates, shortenNames, ...)
+}
+
+
 ##@vcov.sienaFit method for sienaFit
-vcov.sienaFit <- function(object, dropRates=TRUE, shortenNames=TRUE, ...)
+vcov.sienaFit <- function(object, dropRates=TRUE, shortenNames=FALSE, ...)
 {
 	result <- object$covtheta
 	if (shortenNames)
@@ -864,6 +877,13 @@ vcov.sienaFit <- function(object, dropRates=TRUE, shortenNames=TRUE, ...)
 	}
 }
 
+##@print.coef_siena Methods
+print.coef_siena <- function(x, digits=4, ...)
+{
+	print(round(matrix(x,dimnames=list(names(x), "coef ")), digits))
+	invisible(x)
+}
+
 fromObjectToText <- function(a, type='notex'){
 # This is an extended version of the function in sienatable.r
 	b <- as.character(a)

R/sienaGOF.r

@@ -1657,3 +1657,83 @@ egoAlterCovarComb <- function (i, obsData, sims, period, groupName, varName,
 	attr(teax, "EgoAlter") <- TRUE
 	teax
 }
+
+# define spatial autocorrelation functions:
+Moran <- function(x,z) {
+	n <- length(z)
+	z.ave <- mean(z,na.rm=TRUE)
+	numerator <- n*sum(x*outer(z-z.ave,z-z.ave),na.rm=TRUE)
+	denominator <- sum(x,na.rm=TRUE)*sum((z-z.ave)^2,na.rm=TRUE)
+	return(numerator/denominator)
+}
+
+Geary <- function(x,z) {
+	n <- length(z)
+	z.ave <- mean(z,na.rm=TRUE)
+	numerator <- (n-1)*sum(x*(outer(z,z,FUN='-')^2),na.rm=TRUE)
+	denominator <- 2*sum(x,na.rm=TRUE)*sum((z-z.ave)^2,na.rm=TRUE)
+	return(numerator/denominator)
+}
+
+
+
+AC_Moran <- function (i, obsData, sims, period, groupName, varName, depth=3) 
+{
+# An auxiliary function calculating the Moran autocorrelations
+# and rounding to 3 decimals
+	if (length(varName) != 2){
+		stop("AC_Moran expects two varName parameters")
+	}
+	varName1 <- varName[1]
+	varName2 <- varName[2]
+	m <- as.matrix(sparseMatrixExtraction(i, obsData, sims, period, groupName, 
+		varName1))
+	x <- behaviorExtraction(i, obsData, sims, period, groupName, 
+		varName2)
+# Construct a list of powers 1:depth of m
+	if (depth >= 2){
+		mList <- lapply(1:(depth-1), function(i){m})
+		mPowList <- Reduce(function(x,y){pmin(x %*% y,1)}, mList, init=m,accumulate=TRUE)
+		mPowList <- lapply(mPowList, function(mat){mat[!is.na(x), !is.na(x)]})
+		x <- x[!is.na(x)]		
+		Morans <- vapply(mPowList, function(mat){Moran(mat,x)}, FUN.VALUE=0)
+	}
+	else {
+		m <- m[!is.na(x), !is.na(x)]
+		x <- x[!is.na(x)]		
+		Morans <- Moran(m,x) 
+	}
+	names(Morans) <- paste("d=", 1:depth, sep="")
+	round(Morans, 3)
+}
+
+AC_Geary <- function (i, obsData, sims, period, groupName, varName, depth=3) 
+{
+# An auxiliary function calculating the Geary autocorrelations
+# and rounding to 3 decimals
+	if (length(varName) != 2){
+		stop("AC_Geary expects two varName parameters")
+	}
+	varName1 <- varName[1]
+	varName2 <- varName[2]
+	m <- as.matrix(sparseMatrixExtraction(i, obsData, sims, period, groupName, 
+		varName1))
+	x <- behaviorExtraction(i, obsData, sims, period, groupName, 
+		varName2)
+	if (depth >= 2){
+# Construct a list of powers 1:depth of m
+		mList <- lapply(1:(depth-1), function(i){m})
+		mPowList <- Reduce(function(x,y){pmin(x %*% y,1)}, mList, init=m,accumulate=TRUE)
+		mPowList <- lapply(mPowList, function(mat){mat[!is.na(x), !is.na(x)]})
+		x <- x[!is.na(x)]		
+		Gearys <- vapply(mPowList, function(mat){Geary(mat,x)}, FUN.VALUE=0)
+	}
+	else {
+		m <- m[!is.na(x), !is.na(x)]
+		x <- x[!is.na(x)]		
+		Gearys <- Geary(m,x) 
+	}
+	names(Gearys) <- paste("d=", 1:depth, sep="")
+	round(Gearys, 3)
+}
+

docs/manual/RSiena.bib

@@ -3660,6 +3660,8 @@ @incollection{HannekeXing2007
   title={Discrete temporal models of social networks},
   author={Hanneke, Steve and Xing, Eric P.},
   booktitle={Statistical network analysis: Models, issues, and new directions},
+  editor={Airoldi, Edoardo, Blei, David M., Fienberg, Stephen E.,
+                Goldenberg, Anna, Xing, Eric P., and Zheng, Alice X.},
   pages={115--125},
   year={2007},
   publisher={Springer}
@@ -4881,7 +4883,7 @@ @article{Kindermann98
   {U}sing composite social maps to identify peer networks and to study their influences},
   author={Kindermann, Thomas},
   journal={New directions for child development},
-  number={80},
+  volume={81},
   pages={55--82},
   year={1998}
 }
@@ -6163,6 +6165,7 @@ @article{Lyons2011
   journal={Statistics, Politics, and Policy},
   volume={2},
   number={1},
+  pages={1--27},
   year={2011}
 }