[Rsiena-commits] r146 - in pkg: RSiena RSiena/R RSiena/inst/doc RSiena/man RSiena/src RSienaTest RSienaTest/R RSienaTest/doc RSienaTest/inst/doc RSienaTest/man RSienaTest/src

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Mon May 16 16:37:24 CEST 2011 

Author: ripleyrm
Date: 2011-05-16 16:37:22 +0200 (Mon, 16 May 2011)
New Revision: 146

Modified:
   pkg/RSiena/DESCRIPTION
   pkg/RSiena/R/siena08.r
   pkg/RSiena/R/sienaDataCreate.r
   pkg/RSiena/R/sienaDataCreateFromSession.r
   pkg/RSiena/changeLog
   pkg/RSiena/inst/doc/s_man400.pdf
   pkg/RSiena/man/RSiena-package.Rd
   pkg/RSiena/src/Makevars.win
   pkg/RSienaTest/DESCRIPTION
   pkg/RSienaTest/R/siena08.r
   pkg/RSienaTest/R/sienaDataCreate.r
   pkg/RSienaTest/R/sienaDataCreateFromSession.r
   pkg/RSienaTest/changeLog
   pkg/RSienaTest/doc/RSIENAspec.tex
   pkg/RSienaTest/doc/RSiena.bib
   pkg/RSienaTest/doc/RSienaDeveloper.tex
   pkg/RSienaTest/doc/s_man400.tex
   pkg/RSienaTest/doc/simstats0c.tex
   pkg/RSienaTest/inst/doc/s_man400.pdf
   pkg/RSienaTest/man/RSiena-package.Rd
   pkg/RSienaTest/src/Makevars.win
Log:
Fix to Makefile.win to reduce length of link command. Pajek non-directed file input. Other minor changes. 

Modified: pkg/RSiena/DESCRIPTION
===================================================================
--- pkg/RSiena/DESCRIPTION	2011-04-20 12:49:03 UTC (rev 145)
+++ pkg/RSiena/DESCRIPTION	2011-05-16 14:37:22 UTC (rev 146)
@@ -1,8 +1,8 @@
 Package: RSiena
 Type: Package
 Title: Siena - Simulation Investigation for Empirical Network Analysis
-Version: 1.0.12.145
-Date: 2011-04-20
+Version: 1.0.12.146
+Date: 2011-05-16
 Author: Various
 Depends: R (>= 2.9.0), xtable
 Imports: Matrix

Modified: pkg/RSiena/R/siena08.r
===================================================================
--- pkg/RSiena/R/siena08.r	2011-04-20 12:49:03 UTC (rev 145)
+++ pkg/RSiena/R/siena08.r	2011-05-16 14:37:22 UTC (rev 146)
@@ -92,19 +92,22 @@
         {
             if (sum((x1$se < bound)) >= 3)
             {
-                suppressWarnings(check.correl <- cor.test(x1$theta, x1$se, method="spearman"))
-        ## warnings will be given in case of ties, not important here
+                suppressWarnings(check.correl <- cor.test(x1$theta, x1$se,
+                                                          method="spearman"))
+                ## warnings will be given in case of ties, not important here
             }
             else
             {
-                check.correl <- data.frame(estimate=NA, p.value=NA, method="no correlation test")
+                check.correl <- data.frame(estimate=NA, p.value=NA,
+                                           method="no correlation test")
             }
             regfit <- iwlsm(theta ~ 1, psi=psi.iwlsm, data=x1,
                             ses=x1$se^2)
             regfit$terms <- NA
             regfit$model <- NULL
             regfit$psi <- NULL
-        ## symbols ttilde, Qstat, Tsq as in Snijders & Baerveldt (2003), (18), (17), (15)
+            ## symbols ttilde, Qstat, Tsq as in Snijders & Baerveldt (2003),
+            ##(18), (17), (15)
             Tsq <- sum((x1$theta / x1$se)^2)
             regsummary <- summary(regfit)
             tratio <- regsummary$coef[1, 3]
@@ -115,13 +118,13 @@
             cjminus <- -2 * sum(pnorm(x1$theta / x1$se, log=TRUE))
             cjplusp <- 1 - pchisq(cjplus, 2 * nrow(x1))
             cjminusp <- 1 - pchisq(cjminus, 2 * nrow(x1))
-        ## ML estimates and confidence intervals
+            ## ML estimates and confidence intervals
             maxxlik <- maxlik(x1$theta,x1$se)
             cmu  <- confint.mu(x1$theta,x1$se,alpha)
             csig <- confint.sig(x1$theta,x1$se,alpha)
             ret1 <- list(cor.est=check.correl$estimate,
                          cor.pval=check.correl$p.value,
-                         cor.meth=check.correl$method, 
+                         cor.meth=check.correl$method,
                          regfit=regfit, regsummary=regsummary,
                          Tsq=Tsq, pTsq=1 - pchisq(Tsq, nrow(x1) - 1),
                          tratio=tratio,
@@ -237,14 +240,16 @@
            else
            {
                Report(c(": \n", y$cor.meth, " =", format(round(y$cor.est, 4),
-                                                            width=9),
+                                                         width=9),
                         ", two-sided ",reportp(y$cor.pval,3), "\n\n"), sep="",
                       outf)
            }
-           Report("Estimates and test based on IWLS modification of Snijders & Baerveldt (2003)\n",
-                   outf)
-           Report("----------------------------------------------------------------------------\n", 
-                   outf)          
+           Report(c("Estimates and test based on IWLS modification of",
+                    "Snijders & Baerveldt (2003)\n"),
+                  outf)
+           Report(c("---------------------------------------------------",
+                    "-------------------------\n"), sep="",
+                  outf)
            Report(c("Test that all parameters are 0 : \n"), outf)
            Report(c("chi-squared =", format(round(y$Tsq, 4), width=9),
                     ", d.f. = ", y$n1, ", ",
@@ -261,27 +266,30 @@
            Report(c("Chi-squared = ", format(round(y$Qstat, 4), width=9),
                     " (d.f. = ", y$n1-1, "), ", reportp(y$pttilde, 3),
                     "\n\n"), sep="", outf)
-           Report("Estimates and confidence intervals under normality assumptions\n",
-                   outf)
-           Report("--------------------------------------------------------------\n", outf)
+           Report(c("Estimates and confidence intervals under normality",
+                    "assumptions\n"),
+                  outf)
+           Report(c("-------------------------------------------------------",
+                    "-------\n"), outf)
            Report(c("Estimated mean parameter",
-                    format(round(y$mu.ml, 4), width=9), 
-                    " (s.e.",format(round(y$mu.ml.se, 4), width=9), "), two-sided ",
+                    format(round(y$mu.ml, 4), width=9),
+                    " (s.e.",format(round(y$mu.ml.se, 4), width=9),
+                    "), two-sided ",
                     reportp(2 * pt(-abs(y$mu.ml/y$mu.ml.se),
                                    y$n1 - 1), 3), "\n"), sep="", outf)
-           Report(c(format(round(y$mu.confint[3], 2), width=4), 
+           Report(c(format(round(y$mu.confint[3], 2), width=4),
                     "level confidence interval [",
                     format(round(y$mu.confint[1], 4), width=7),
-                    ",", 
+                    ",",
                     format(round(y$mu.confint[2], 4), width=7), "]\n"), outf)
            Report(c("Estimated standard deviation",
-                    ifelse((y$sigma.ml > 0.0001)|(y$sigma.ml < 0.0000001), 
-                           format(round(y$sigma.ml, 4), width=9), " < 0.0001"),       
+                    ifelse((y$sigma.ml > 0.0001)|(y$sigma.ml < 0.0000001),
+                           format(round(y$sigma.ml, 4), width=9), " < 0.0001"),
                      "\n"), outf)
-           Report(c(format(round(y$sigma.confint[3], 2), width=4), 
+           Report(c(format(round(y$sigma.confint[3], 2), width=4),
                     "level confidence interval [",
                     format(round(y$sigma.confint[1], 4), width=7),
-                    ",", 
+                    ",",
                     format(round(y$sigma.confint[2], 4), width=7), "]\n\n"), outf)
            Report("Fisher's combination of one-sided tests\n", outf)
            Report("----------------------------------------\n", outf)
@@ -362,8 +370,8 @@
 plot.sienaMeta <- function(x, ..., layout = c(2,2))
 {
     library(lattice)
-    tmp <- xyplot(theta ~ se|effects, 
-                  data=x$thetadf[is.na(x$thetadf$scoretests),], 
+    tmp <- xyplot(theta ~ se|effects,
+                  data=x$thetadf[is.na(x$thetadf$scoretests),],
                   ylab="estimates",
                   xlab="standard errors", layout=layout,
                   panel=function(x, y)
@@ -371,7 +379,7 @@
                   panel.xyplot(x, y)
                   panel.abline(0, qnorm(0.025))
                   panel.abline(0, qnorm(0.975))
-              },  
+              },
                   prepanel=function(x,y)
               {   list(xlim=c(min(0,min(x)),max(0,max(x))),
                        ylim=c(min(0,min(y)),max(0,max(y))))

Modified: pkg/RSiena/R/sienaDataCreate.r
===================================================================
--- pkg/RSiena/R/sienaDataCreate.r	2011-04-20 12:49:03 UTC (rev 145)
+++ pkg/RSiena/R/sienaDataCreate.r	2011-05-16 14:37:22 UTC (rev 146)
@@ -708,10 +708,12 @@
                     if (sparse)
                     {
                         mymat <- myarray[[j]]
+                        diag(mymat) <- NA
                     }
                     else
                     {
                         mymat <- myarray[, , j]
+                        diag(mymat) <- NA
                     }
                     if (suppressMessages(!isSymmetric(mymat)))
                     {
@@ -1005,16 +1007,19 @@
         rvals <- range(vals,na.rm=TRUE)
     }
     rvals1 <- rvals[2] - rvals[1]
-    tmp <- apply(vals, 2, function(v){
-    sapply(1: length(v), function(x, y, r){
-        z <- y
-        z[x] <- NA
-        #browser()
-        tmp1 <- 1 - abs(y[x] - z) / r
-        list(sum(tmp1, na.rm=TRUE), sum(!is.na(tmp1)))
-         },
-           y=v, r=rvals1)})
-
+    tmp <- apply(vals, 2, function(v)
+             {
+                 sapply(1: length(v), function(x, y, r)
+                    {
+                        z <- y
+                        z[x] <- NA
+                        ##browser()
+                        tmp1 <- 1 - abs(y[x] - z) / r
+                        list(sum(tmp1, na.rm=TRUE), sum(!is.na(tmp1)))
+                    },
+                        y=v, r=rvals1)
+             }
+                 )
     tmp <- unlist(tmp)
     raw <- tmp[seq(1, length(tmp), by=2)]
     cnts <- tmp[seq(2, length(tmp), by=2)]

Modified: pkg/RSiena/R/sienaDataCreateFromSession.r
===================================================================
--- pkg/RSiena/R/sienaDataCreateFromSession.r	2011-04-20 12:49:03 UTC (rev 145)
+++ pkg/RSiena/R/sienaDataCreateFromSession.r	2011-05-16 14:37:22 UTC (rev 146)
@@ -380,6 +380,12 @@
                                               c(nonzero[[x]], 10, 11)), 3] <- 0
                                myedgelist[myedgelist[,3] %in%
                                           nonzero[[x]], 3] <- 1
+                               if (!is.directed(namefiles[[x]]))
+                               {
+                                   perm <- c(2, 1, 3)
+                                   myedgelist <- rbind(myedgelist, myedgelist[, perm])
+                               }
+                             
                                if (network.size(namefiles[[x]]) != nActors)
                                    stop("number of actors inconsistent")
 

Modified: pkg/RSiena/changeLog
===================================================================
--- pkg/RSiena/changeLog	2011-04-20 12:49:03 UTC (rev 145)
+++ pkg/RSiena/changeLog	2011-05-16 14:37:22 UTC (rev 146)
@@ -1,3 +1,16 @@
+2011-05-16 R-forge revision 146
+
+	* src/Makevars.win: alter linking to reduce command line length
+	* doc/s_man400.tex: add tex code to reduce size of pdf, many
+	updates
+	* doc/RSiena.bib, doc/simstatsc.tex, doc/RSienaDeveloper.tex:
+	updated documentation for symmetric networks and other minor changes.
+	* R/siena08.r: formatting changes only
+	* R/sienaDataCreate.r: set diagonals to NA for sparse matrices
+	when calculating degree and setting attributes
+	* R/sienaDataCreateFromSession.r: if using read.pajek to read a
+	non-directed network duplicate the ties in the edgelist.
+
 2011-04-20 R-forge revision 145
 
 	* src/model/effects/outTruncEffect.cpp: reformating

Modified: pkg/RSiena/inst/doc/s_man400.pdf
===================================================================
--- pkg/RSiena/inst/doc/s_man400.pdf	2011-04-20 12:49:03 UTC (rev 145)
+++ pkg/RSiena/inst/doc/s_man400.pdf	2011-05-16 14:37:22 UTC (rev 146)
@@ -1,628 +1,61 @@
-%PDF-1.4
+%PDF-1.5
 %ÐÔÅØ
-1 0 obj
-<< /S /GoTo /D (section.1) >>
+2 0 obj <<
+/Type /ObjStm
+/N 100
+/First 814
+/Length 1537      
+/Filter /FlateDecode
+>>
+stream
+xڝWMoÛ8½ûWÌm›CS‰¤(©(
+IZØî.šìîY‘h›[I4$*ÿ¾ohÓNÐ&r÷hLiÞ|¼Ç!“RBÉ„4eŠJ*RJ*KJ%¥E©ÆZNi©)-H¤þHdÉB’BÁ$©ñФ`ÂG逘᝔”áT”9Éœ´À£ ­ñuJy¢JP®rRåøDi* ¯I†”*
+ at H*…	æ@B.Iʈxâ#N/)õBJÓ<%DOE‚uä+2AU@ç	ŠB†9*“:AT<K$<…ìsà©|Û‚,U‹xr-€—Á© žn<ÂJàià—ÀÓø¸^ž yÀËQ	¼e!YE²H 	¯à¯¯€Y†€–¼‚î§e( ’Ë(U$Jrq08Ë@»2©J)¨‚ã0Bò+
+#”^’	ךÀ\<%w´Yð
+UÊ+ at VX(­èŒ‚[äŒÝA‘ȸ8$¸)hyRp»`pª J„JA–(jB<Qr@—(e¾HÁ—(™Œ vcÈ^È[&Üwp&9M4—Ö¤`U‚6¨W
+Lˆ“øh‘‚	+@–¬¼–Š› ò¤RŠ»ƒ©}’¥ŠöÃÈyÈšC H©¹mè,`²Å‡ôîšÞ}v7ŽÞ]ЛÑÔÞºþ4=¡oRúlz3T-Ù~醮â—'?xmªÁG—+úb{ÛÁåª÷ƒ;y1„Ø~/Â{Û¯hô€1
+Ý[¿¦ë«Ë?Îè'ÞÓí †„A•¯h›â8ãŸ
+¤ˆ mÊ¢ªoh˜úžsñkC«¡Ú¬mJ¦Ñè€7òª
+M}ƒßÿÚ¾q÷/{ï'gú÷8`9¸Ž¾T5¹~·ýôpLCY(ìëu¼§Î
+†ã+ÛU‡<„tÉ8ƒ[zŒ»:¸«g^ŽÞnµE
+ùvÇÀe¸Œ.¶U[Ò
+ƒáðH×õ`L > j:w=T9ÅÍ>Åuí{$wLo•Ì¢¶=}ÏCä“>A~íFC÷kG[»Zûö‘–Ug[[
+Ûs´8@‹'ÐË©^íú;3ŒUïñP/*æÖû¡êGÈ:žæõîbw6àÜÞÝKHÑYOæ¡ê6­¡¯4ÖƒÝx ´z>Nf ÷"ÊèÏÉ·¶7,¡Û´\mši03@{ñèïÝÔzËÙ„q4sµå!§ko6c¨¦uî£Už3r|O—¦žü^[§3¸EÄ-è³½c·Á,Í`úz6¥2º–û)½6íf+ÔuÛšn|á<ØIíê
+ý€ª~#ð;UíËÂNI2Î b˜ñåïwZP˜â›ÉSƒ-ÿj9*n,Åç…
+j^´´­™€ðz ˆúþT¤[ãï1hP¦ìC8ML³2ÔÚÑ¿~2=!1„0LµŸpcbR›¡ƒDº«Úi†=u@tñX5¶Æ.»«[ùYW]%ºÛ@5
+¨;Þ=RsÊä é*¼CSšm*þY÷Âà>>‹ð<÷7Ç1FÖ6ˆÛvCGËvì
+Ê£WŽ¢Û¸Ý «×U¿23¾Eô-èÜìÏ—Õ½«1£/®1-SÛ%†çì”E•Â +ä8xžèã^Id–K|»/=Të†o`¥ÇiRcº¸Þ¼í3¾g¢‰MüŸhøýKÑdŒ†È+ÀT£«YK»ûä‘ÚÊ¢taÐùàÆñm„~ZÇ>T»ŸóGV‰…xcaz¬«;hsçÚé’u„ÑtÖ4A†áš¾ßm1á¹™„ƒb4kæGŒŸöx&Á<bætc;ƒƒ°n…ÿ'¬D¢ÔacÈW¿šÃ+"^;qg}¼UtÕƒí¦ŽÜä³Â]ïå=µë™~rá|5è¾1Ü–›g·@\™úm‹Fkú*ÉçÚ¬ÇG0ÑfÔ Êþ	£<ŒÆóp[ñÉLçkS›ÉND<-¶ûýWópê1e‚D¹M!ÍOÖ“»ý 3È2"K:kWnÀêf\TtQ|“‰|²ø	Ñý×
+endstream
 endobj
-4 0 obj
-(1 General information)
-endobj
-5 0 obj
-<< /S /GoTo /D (part.1) >>
-endobj
-8 0 obj
-(I Minimal Intro)
-endobj
-9 0 obj
-<< /S /GoTo /D (section.2) >>
-endobj
-12 0 obj
-(2 Getting started with SIENA )
-endobj
-13 0 obj
-<< /S /GoTo /D (subsection.2.1) >>
-endobj
-16 0 obj
-(2.1 Data formats)
-endobj
-17 0 obj
-<< /S /GoTo /D (subsection.2.2) >>
-endobj
-20 0 obj
-(2.2 Installation and running the graphical user interface under Windows)
-endobj
-21 0 obj
-<< /S /GoTo /D (subsubsection.2.2.1) >>
-endobj
-24 0 obj
-(2.2.1 Using the graphical user interface from Mac or Linux)
-endobj
-25 0 obj
-<< /S /GoTo /D (subsubsection.2.2.2) >>
-endobj
-28 0 obj
-(2.2.2 Running the graphical user interface: more details)
-endobj
-29 0 obj
-<< /S /GoTo /D (subsubsection.2.2.3) >>
-endobj
-32 0 obj
-(2.2.3 Entering Data.)
-endobj
-33 0 obj
-<< /S /GoTo /D (subsubsection.2.2.4) >>
-endobj
-36 0 obj
-(2.2.4 Running the Estimation Program)
-endobj
-37 0 obj
-<< /S /GoTo /D (subsubsection.2.2.5) >>
-endobj
-40 0 obj
-(2.2.5 Details of The Data Entry Screen)
-endobj
-41 0 obj
-<< /S /GoTo /D (subsubsection.2.2.6) >>
-endobj
-44 0 obj
-(2.2.6 Continuing the estimation)
-endobj
-45 0 obj
-<< /S /GoTo /D (subsection.2.3) >>
-endobj
-48 0 obj
-(2.3 Using SIENA within R)
-endobj
-49 0 obj
-<< /S /GoTo /D (subsubsection.2.3.1) >>
-endobj
-52 0 obj
-(2.3.1 For those who are slightly familiar with R)
-endobj
-53 0 obj
-<< /S /GoTo /D (subsubsection.2.3.2) >>
-endobj
-56 0 obj
-(2.3.2 For those fully conversant with R)
-endobj
-57 0 obj
-<< /S /GoTo /D (subsubsection.2.3.3) >>
-endobj
-60 0 obj
-(2.3.3 The transition from using the graphical user interface to commands)
-endobj
-61 0 obj
-<< /S /GoTo /D (subsection.2.4) >>
-endobj
-64 0 obj
-(2.4 An example R script for getting started)
-endobj
-65 0 obj
-<< /S /GoTo /D (subsection.2.5) >>
-endobj
-68 0 obj
-(2.5 Outline of estimation procedure)
-endobj
-69 0 obj
-<< /S /GoTo /D (subsection.2.6) >>
-endobj
-72 0 obj
-(2.6 Using multiple processes)
-endobj
-73 0 obj
-<< /S /GoTo /D (subsection.2.7) >>
-endobj
-76 0 obj
-(2.7 Steps for looking at results: Executing SIENA.)
-endobj
-77 0 obj
-<< /S /GoTo /D (subsection.2.8) >>
-endobj
-80 0 obj
-(2.8 Giving references)
-endobj
-81 0 obj
-<< /S /GoTo /D (subsection.2.9) >>
-endobj
-84 0 obj
-(2.9 Getting help with problems)
-endobj
-85 0 obj
-<< /S /GoTo /D (part.2) >>
-endobj
-88 0 obj
-(II Users' manual)
-endobj
-89 0 obj
-<< /S /GoTo /D (section.3) >>
-endobj
-92 0 obj
-(3 Program parts)
-endobj
-93 0 obj
-<< /S /GoTo /D (section.4) >>
-endobj
-96 0 obj
-(4 Input data)
-endobj
-97 0 obj
-<< /S /GoTo /D (subsection.4.1) >>
-endobj
-100 0 obj
-(4.1 Digraph data files)
-endobj
-101 0 obj
-<< /S /GoTo /D (subsubsection.4.1.1) >>
-endobj
-104 0 obj
-(4.1.1 Transformation between matrix and edge list formats)
-endobj
-105 0 obj
-<< /S /GoTo /D (subsubsection.4.1.2) >>
-endobj
-108 0 obj
-(4.1.2 Structurally determined values)
-endobj
-109 0 obj
-<< /S /GoTo /D (subsection.4.2) >>
-endobj
-112 0 obj
-(4.2 Dyadic covariates)
-endobj
-113 0 obj
-<< /S /GoTo /D (subsection.4.3) >>
-endobj
-116 0 obj
-(4.3 Individual covariates)
-endobj
-117 0 obj
-<< /S /GoTo /D (subsection.4.4) >>
-endobj
-120 0 obj
-(4.4 Interactions and dyadic transformations of covariates)
-endobj
-121 0 obj
-<< /S /GoTo /D (subsection.4.5) >>
-endobj
-124 0 obj
-(4.5 Dependent action variables)
-endobj
-125 0 obj
-<< /S /GoTo /D (subsection.4.6) >>
-endobj
-128 0 obj
-(4.6 Missing data)
-endobj
-129 0 obj
-<< /S /GoTo /D (subsection.4.7) >>
-endobj
-132 0 obj
-(4.7 Composition change)
-endobj
-133 0 obj
-<< /S /GoTo /D (subsection.4.8) >>
-endobj
-136 0 obj
-(4.8 Centering)
-endobj
-137 0 obj
-<< /S /GoTo /D (section.5) >>
-endobj
-140 0 obj
-(5 Model specification)
-endobj
-141 0 obj
-<< /S /GoTo /D (subsection.5.1) >>
-endobj
-144 0 obj
-(5.1 Important structural effects for network dynamics: one-mode networks)
-endobj
-145 0 obj
-<< /S /GoTo /D (subsection.5.2) >>
-endobj
-148 0 obj
-(5.2 Important structural effects for network dynamics: two-mode networks)
-endobj
-149 0 obj
-<< /S /GoTo /D (subsection.5.3) >>
-endobj
-152 0 obj
-(5.3 Effects for network dynamics associated with covariates)
-endobj
-153 0 obj
-<< /S /GoTo /D (subsection.5.4) >>
-endobj
-156 0 obj
-(5.4 Cross-network effects for dynamics of multiple networks)
-endobj
-157 0 obj
-<< /S /GoTo /D (subsection.5.5) >>
-endobj
-160 0 obj
-(5.5 Effects on behavior evolution)
-endobj
-161 0 obj
-<< /S /GoTo /D (subsection.5.6) >>
-endobj
-164 0 obj
-(5.6 Additional interaction effects)
-endobj
-165 0 obj
-<< /S /GoTo /D (subsubsection.5.6.1) >>
-endobj
-168 0 obj
-(5.6.1 Interaction effects for network dynamics)
-endobj
-169 0 obj
-<< /S /GoTo /D (subsection.5.7) >>
-endobj
-172 0 obj
-(5.7 Time heterogeneity in model parameters)
-endobj
-173 0 obj
-<< /S /GoTo /D (subsection.5.8) >>
-endobj
-176 0 obj
-(5.8 Limiting the maximum outdegree)
-endobj
-177 0 obj
-<< /S /GoTo /D (section.6) >>
-endobj
-180 0 obj
-(6 Estimation)
-endobj
-181 0 obj
-<< /S /GoTo /D (subsection.6.1) >>
-endobj
-184 0 obj
-(6.1 The estimation function siena07)
-endobj
-185 0 obj
-<< /S /GoTo /D (subsubsection.6.1.1) >>
-endobj
-188 0 obj
-(6.1.1 Initial Values and Convergence Check)
-endobj
-189 0 obj
-<< /S /GoTo /D (subsection.6.2) >>
-endobj
-192 0 obj
-(6.2 Some important components of the sienaFit object)
-endobj
-193 0 obj
-<< /S /GoTo /D (subsection.6.3) >>
-endobj
-196 0 obj
-(6.3 Algorithm)
-endobj
-197 0 obj
-<< /S /GoTo /D (subsection.6.4) >>
-endobj
-200 0 obj
-(6.4 Output)
-endobj
-201 0 obj
-<< /S /GoTo /D (subsubsection.6.4.1) >>
-endobj
-204 0 obj
-(6.4.1 Fixing parameters)
-endobj
-205 0 obj
-<< /S /GoTo /D (subsubsection.6.4.2) >>
-endobj
-208 0 obj
-(6.4.2 Automatic fixing of parameters)
-endobj
-209 0 obj
-<< /S /GoTo /D (subsubsection.6.4.3) >>
-endobj
-212 0 obj
-(6.4.3 Conditional and unconditional estimation)
-endobj
-213 0 obj
-<< /S /GoTo /D (subsubsection.6.4.4) >>
-endobj
-216 0 obj
-(6.4.4 Required changes from conditional to unconditional estimation)
-endobj
-217 0 obj
-<< /S /GoTo /D (section.7) >>
-endobj
-220 0 obj
-(7 Standard errors)
-endobj
-221 0 obj
-<< /S /GoTo /D (section.8) >>
-endobj
-224 0 obj
-(8 Tests)
-endobj
-225 0 obj
-<< /S /GoTo /D (subsection.8.1) >>
-endobj
-228 0 obj
-(8.1 Wald-type tests)
-endobj
-229 0 obj
-<< /S /GoTo /D (subsection.8.2) >>
-endobj
-232 0 obj
-(8.2 Score-type tests)
-endobj
-233 0 obj
-<< /S /GoTo /D (subsection.8.3) >>
-endobj
-236 0 obj
-(8.3 Example: one-sided tests, two-sided tests, and one-step estimates)
-endobj
-237 0 obj
-<< /S /GoTo /D (subsubsection.8.3.1) >>
-endobj
-240 0 obj
-(8.3.1 Multi-parameter tests)
-endobj
-241 0 obj
-<< /S /GoTo /D (subsection.8.4) >>
-endobj
-244 0 obj
-(8.4 Alternative application: convergence problems)
-endobj
-245 0 obj
-<< /S /GoTo /D (subsection.8.5) >>
-endobj
-248 0 obj
-(8.5 Testing differences between independent groups)
-endobj
-249 0 obj
-<< /S /GoTo /D (subsection.8.6) >>
-endobj
-252 0 obj
-(8.6 Testing time heterogeneity in parameters)
-endobj
-253 0 obj
-<< /S /GoTo /D (section.9) >>
-endobj
-256 0 obj
-(9 Simulation)
-endobj
-257 0 obj
-<< /S /GoTo /D (subsection.9.1) >>
-endobj
-260 0 obj
-(9.1 Accessing the generated networks)
-endobj
-261 0 obj
-<< /S /GoTo /D (subsection.9.2) >>
-endobj
-264 0 obj
-(9.2 Conditional and unconditional simulation)
-endobj
-265 0 obj
-<< /S /GoTo /D (section.10) >>
-endobj
-268 0 obj
-(10 Getting started)
-endobj
-269 0 obj
-<< /S /GoTo /D (subsection.10.1) >>
-endobj
-272 0 obj
-(10.1 Model choice)
-endobj
-273 0 obj
-<< /S /GoTo /D (subsubsection.10.1.1) >>
-endobj
-276 0 obj
-(10.1.1 Exploring which effects to include)
-endobj
-277 0 obj
-<< /S /GoTo /D (subsection.10.2) >>
-endobj
-280 0 obj
-(10.2 Convergence problems)
-endobj
-281 0 obj
-<< /S /GoTo /D (section.11) >>
-endobj
-284 0 obj
-(11 Multilevel network analysis)
-endobj
-285 0 obj
-<< /S /GoTo /D (subsection.11.1) >>
-endobj
-288 0 obj
-(11.1 Multi-group Siena analysis)
-endobj
-289 0 obj
-<< /S /GoTo /D (subsection.11.2) >>
-endobj
-292 0 obj
-(11.2 Meta-analysis of Siena results)
-endobj
-293 0 obj
-<< /S /GoTo /D (subsubsection.11.2.1) >>
-endobj
-296 0 obj
-(11.2.1 Meta-analysis directed at the mean and variance of the parameters)
-endobj
-297 0 obj
-<< /S /GoTo /D (subsubsection.11.2.2) >>
-endobj
-300 0 obj
-(11.2.2 Meta-analysis directed at testing the parameters)
-endobj
-301 0 obj
-<< /S /GoTo /D (subsubsection.11.2.3) >>
-endobj
-304 0 obj
-(11.2.3 Contrast between the two kinds of meta-analysis )
-endobj
-305 0 obj
-<< /S /GoTo /D (section.12) >>
-endobj
-308 0 obj
-(12 Formulas for effects)
-endobj
-309 0 obj
-<< /S /GoTo /D (subsection.12.1) >>
-endobj
-312 0 obj
-(12.1 Network evolution)
-endobj
-313 0 obj
-<< /S /GoTo /D (subsubsection.12.1.1) >>
-endobj
-316 0 obj
-(12.1.1 Network evaluation function)
-endobj
-317 0 obj
-<< /S /GoTo /D (subsubsection.12.1.2) >>
-endobj
-320 0 obj
-(12.1.2 Multiple network effects)
-endobj
-321 0 obj
-<< /S /GoTo /D (subsubsection.12.1.3) >>
-endobj
-324 0 obj
-(12.1.3 Network endowment function)
-endobj
-325 0 obj
-<< /S /GoTo /D (subsubsection.12.1.4) >>
-endobj
-328 0 obj
-(12.1.4 Network rate function)
-endobj
-329 0 obj
-<< /S /GoTo /D (subsection.12.2) >>
-endobj
-332 0 obj
-(12.2 Behavioral evolution)
-endobj
-333 0 obj
-<< /S /GoTo /D (subsubsection.12.2.1) >>
-endobj
-336 0 obj
-(12.2.1 Behavioral evaluation function)
-endobj
-337 0 obj
-<< /S /GoTo /D (subsubsection.12.2.2) >>
-endobj
-340 0 obj
-(12.2.2 Behavioral endowment function)
-endobj
-341 0 obj
-<< /S /GoTo /D (subsubsection.12.2.3) >>
-endobj
-344 0 obj
-(12.2.3 Behavioral rate function)
-endobj
-345 0 obj
-<< /S /GoTo /D (section.13) >>
-endobj
-348 0 obj
-(13 Parameter interpretation)
-endobj
-349 0 obj
-<< /S /GoTo /D (subsection.13.1) >>
-endobj
-352 0 obj
-(13.1 Longitudinal models)
-endobj
-353 0 obj
-<< /S /GoTo /D (subsubsection.13.1.1) >>
-endobj
-356 0 obj
-(13.1.1 Ego \205 alter selection tables)
-endobj
-357 0 obj
-<< /S /GoTo /D (subsubsection.13.1.2) >>
-endobj
-360 0 obj
-(13.1.2 Ego \205 alter influence tables)
-endobj
-361 0 obj
-<< /S /GoTo /D (part.3) >>
-endobj
-364 0 obj
-(III Programmers' manual)
-endobj
-365 0 obj
-<< /S /GoTo /D (section.14) >>
-endobj
-368 0 obj
-(14 Get the source code)
-endobj
-369 0 obj
-<< /S /GoTo /D (section.15) >>
-endobj
-372 0 obj
-(15 Other tools you need)
-endobj
-373 0 obj
-<< /S /GoTo /D (section.16) >>
-endobj
-376 0 obj
-(16 Building, installing and checking the package)
-endobj
-377 0 obj
-<< /S /GoTo /D (section.17) >>
-endobj
-380 0 obj
-(17 Adding an effect)
-endobj
-381 0 obj
-<< /S /GoTo /D (subsection.17.1) >>
-endobj
-384 0 obj
-(17.1 Example: adding the truncated out-degree effect)
-endobj
-385 0 obj
-<< /S /GoTo /D (appendix.A) >>
-endobj
-388 0 obj
-(A List of Functions in Order of Execution)
-endobj
-389 0 obj
-<< /S /GoTo /D (appendix.B) >>
-endobj
-392 0 obj
-(B Changes compared to earlier versions)
-endobj
-393 0 obj
-<< /S /GoTo /D (appendix.C) >>
-endobj
-396 0 obj
-(C References)
-endobj
-408 0 obj <<
-/Length 1172      
+410 0 obj <<
+/Length 1170      
 /Filter /FlateDecode
 >>
 stream
-xڝVKsÛ6¾ëWðH΄ |´''qÒtj7µÔSÒDÁj>T’²£þúîbIU’•É8£\ì~ûÞ%Ö>Ìøwžo³×ïEHŲ<Áâ><e\‰ M9SÁb|oLÉ4Ü™*Š.Ãû¶‹þZü
-’ù±¤)KÄIênîlcˆQñ@(–¨T"cœ,•Y `,bdß
-€=7ŸYx綕Ý#@çL£€9Zµˆr¶5ñ^±7Œ¤çû{e»žä„fYªN?E `v•ë¼È§Î–άZzû­ÝF1pØÿ·]°Bk²½à,OÑöœ¥Z⟍{DPPë<ì	ª½§çï_!d«Ÿ¢X%:|g·¦jÛ ãp̘…óÁ.aÅîDèÊþgººÝ}á"µÕŠ$Þ¶Ue×Ö{)dÆTV€—ÓIA6]m;W¯(^†äB Ä³:¸^ÌÀÓ@dš¥JU<ÊzöÏ,ñ—ôï	÷Hxý¾Á»vöüα'ÖxBŽ }Bµ¬Heêë/ƒâȱ°SPšä̲:S y‹4xÐ#r&ò±¼æ¯o¯(¡ùs"€UL%û…k~(îPQ0	0òÍ]½« SmqUiø±y´ýàÖR=É<ìèþºÞºÎ•¾àõÖú"yBb{ ‹«ÆTûÞõÏí”`h!ì$¼^¡×²­·»ÁŽj·]SÈ\2%¬ä”P֝ÁîÉÓpؘN¥é:g4ÏÂv7L÷–=Ö'xJ® Ý®'·Qäžè548¶‚¶XË5²`€OQí£Dµ›pƆ æ¾õ½íYyOøèÂØx
-F2#Ù=€©uhÊÚÍ5kzÚñ‰ú¤VájߘڕóÐvq^7ˆ2ØÑ'lEï`‘/>Æqã¿RA·žÑî>Ì‚Ï^Õñ4:¬¿Ó¾Ú^ˆ	ÌÅVøêå†iÒç@XV/˸÷2¾”ïzœ*´XJ„»bç±ÀëŒEvÙ…X	šfõR_Ð’CƼ¹d¶ºlö¦PðKfÃþ‚¥.6nÔíÆÐQŸ ¡6¾DiÃÅåQ•ðœI•fÕ7_~XÕ¾ÿpyAûùy‘(Î.Üãd*Ü"*‡X`W&Jô€%´º`ƒ†®“K_'C-g™8µýi	ælH
-8M4¶Ô¥[î|«"qk¼ÄC¤ÓЬ-‡ÑFŠNgöý`ëÖägª8XÿÜð”Á"Ÿî¡-6vŠ]ÆdqºãÌ)I^ásizt8ùðéíU:Æt•ÃQŽÔs€om)Éx¦¾—z	kQ^ʽ‡N°0ÍÍhåM*q”0®€œLk¾%¬—“5C¹xd‡@=un,*ƒu{÷ži!ˉ·p³Ä·=ÝÝÜ–xúeçzàDs3ÞŒeclE×ó—ìæ°¬ó K?Öm·¶—L¦Aq>»Þn:,ƒ)IàÓÌ®«QÇé,Àè
-Î
-^Ðg0îZhùXMŒA8Úð¹õi¢Õ7
+xڝVKsÛ6¾ëWðHÍ„  ÙžœÄIÓ©ÝÔVOI0K¨ùPIÊŽú뻋%UIV&ãŒfDØý°owÉ£UÄ£3þç›Åìõ{‘ER±,ÏD´¸$7Œ+ÙŠËès|e›¹4ñÖVó$å2¾o»ù_‹_A3?ÔÂ0[œ´nn½k,	*	ÅRe$
+&¦`Ff€±TˆQ|;¬î¹bøÌâ¿©Ü¢$g$(ÈѪÅ<—q[“ì{ÃHû¶ñ/]דžÐ,3êXñÓì¶ò`]PùÔ¹ÒÛeKo¿µ›yîßÿm¬Ðšl/8Ë
+Úž3£5!þÙøG…ký€‹Aµ÷ôüý+„lùÓ<Q©Žß¹í†Ú5(8
+fñí`?q?Oœ‰Ø—ýÏtt½ýÂ…qÕ’4Þ¶UåV.x)dÁT
+Nƒ›)gvýŠ’*ψp¹˜	X€«‘È438žªÂDe=ûg–†Cú“ô¸ñú}-¢wíìøbO¢É„œ@Ý
+Vi3`GŽÌR,ݹ¸ë‡Î–ÃYã@ $¤¸GäLä#ÂíÇËëÊh~ œ
+g¿pÍ÷ì>“À€QîÖ×Û
+RÕ6WeâÍ£ë¿ÚoeP$s™Ç_Ößù2¼^»À’'” ±:¸hlµë}ÿÜN	†òÀNA ®³ôZ¶õf;¸ñÚM×&T2—LgÀ¢2¡¬:‹å“›xXہV¥í:ï4Ïâv;LçŽ=<%W`Ý®'·Qåžök¨&pl	vHæŠX"àcT÷"Qm'œ±"@¸oC1B}VÁ>º0Ò¼ÁHæc$»¸AjÛ²„zóÍŠ^‡v|â}R«x¹klíËIxh»¤¯DÜ’ö'\Eï`Q ãô¸ñ_©¨[EÏön>Ì¢ÏáªÃv´'l8Ӂm/Ä„
+æâ+~õrÃ4éS ¤ÕËÁ2¼LŽò3R,¸ž¤…ŠR©€pWì4xüƒ±Èλ(ÁcÛ,_êZ²ÏX0—ÌVçÍþÑ
+~Îl`0ãÅڏwû1tT'°QÛ@QÄpp¾U¥<gReû^õÍÆ—ïgu¨?œ^P~¡_¤Š3÷0™
+§ˆÊ!X•©ÒÐ-`
+-ÏØ ¡‡ëôܧÀQSËY&öMmDZCe‚9kº‚œ¦7¶T¥¿Û†RÅ͍
+smb»r´9Œ6Rô`qÜ»pc×®>c=tz˜O{ëŸn`ÞêéœÚbí¦ØeLÇ¡;Ìœ’ä>ïlNà;>ƒ½JBÅØ®òØÊq÷à[SJ2ž©ï¥^†±x&÷:ÅúÁ47£e”o4©ÄV>fÀúftr2ø”Л|§\<ŠC ž:?/ƒusç®i
+¡È‘·pr‡o;:»²8-qõËÖ÷ ‰æf*¾ic]EÇ·%Ùõ~>8@ïB[wÝÊuA3Åiïz»î.'RšÂ·™[Uãǽ £+8+xAßÁ8k¡ä
+{fü¼=nÚð¹õèÔç
 endstream
 endobj
-407 0 obj <<
-/Type /Page
-/Contents 408 0 R
-/Resources 406 0 R
-/MediaBox [0 0 595.276 841.89]
-/Parent 418 0 R
-/Annots [ 399 0 R 400 0 R 401 0 R 402 0 R 417 0 R 403 0 R 404 0 R 405 0 R ]
->> endobj
-398 0 obj <<
+400 0 obj <<
 /Type /XObject
 /Subtype /Form
 /BBox [0 0 84 59.04]
 /FormType 1
 /Matrix [1 0 0 1 0 0]
-/Resources 419 0 R
+/Resources 421 0 R
 /Length 34        
 /Filter /FlateDecode
 >>
@@ -630,7 +63,7 @@
 xÚ+ä²0Q0 BSK=+9—Kß3×PÁ%Ÿ+ hƐ
 endstream
 endobj
-397 0 obj <<
+399 0 obj <<
 /Type /XObject
 /Subtype /Image
 /Width 350
@@ -742,891 +175,130 @@
 klŠÇ,T‚ÄñéïœöšwŒ¬u?ÜèéÒÃ$V¾gžedc#ýsÏqELè¯N)FËìžkñöñýÄrF|¤ùWýcm1ç’zyÅvZ݇‡´X®`Ži“P˜IG䟽*¤–là}­VU7F•Ÿî`‡i¾ñ^‡u}®A«X%õÖö”iCŒîÁ,3ù*í£I.—PŠÜ^E’[`ÊsŽ³»oÖŠ*’»ÔâÄI·qñ¨Ž@¢ghÔgcÅçýìdþ5*̆åc0)9#~pqôQV`N—$U’B6Ÿ½‚qÛŸZS~(wF¢ŠdûhôoÒ—í‹ýÖý(¢˜‡}´z7ä(ûhôoÈQE 'ÛÇ£þuêI[¶¹ö¢ŠC3ï5–HX“"û!Ï®<}­«4ÛyÁÄ’Ü8'qÀíùQEsÔo”î¥N=‡Íã‹-ý"m*iå’%ie{¢Ä‚áGÞ8ëÛëX?¼Wq{cc X㍘͔ˆãa^I8á‡OOJ(¬èÉË–çM*qU£dqÖšÄÒͪê3©šcgå³™][-²0ùæ<ŒƒüñSiz–§¨É#›¶.»9;Xgv aÎ3’}I'©4Q]5"¹Né¥ïoí®´’é}2Jó¡d1ƒ˜ðë–Và$§å⡳Ôtý:Ú(šÖå¯×y–â;‚£Ë={òxêh¢¢ÊÖ#x»”­5(gÕÑ䀮ùÃKµ˜åsÐç?t‡ÃãSH¼©DQÉ™×÷i€F9ùØŽ»ºz‘E,•‰«'1óx¾¶µ¤Ë$‰!o>uPOUè½°?Ö3OÞÝ´H…Š†UP3…àsù÷¢Šå¨­5c	ll®§›g Œ’Ö Ilc!Kc Øé¥áfW(Ós¾@z{ô¢Šê„VÇö¹ÿÙ
 endstream
 endobj
-419 0 obj <<
-/XObject << /Im1 397 0 R >>
-/ProcSet [ /PDF /ImageC ]
->> endobj
-399 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [370.153 198.838 406.822 210.793]
-/A << /S /GoTo /D (cite.Snijders01) >>
->> endobj
-400 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [411.241 198.838 433.159 210.793]
-/A << /S /GoTo /D (cite.Snijders01) >>
->> endobj
-401 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [436.472 198.838 458.39 210.793]
-/A << /S /GoTo /D (cite.Snijders05) >>
->> endobj
-402 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [465.734 198.838 487.928 210.793]
-/A << /S /GoTo /D (cite.SnijdersEA07) >>
->> endobj
-417 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [115.285 186.883 161.749 198.838]
-/A << /S /GoTo /D (cite.SnijdersEA07) >>
->> endobj
-403 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [167.561 186.883 189.479 198.838]
-/A << /S /GoTo /D (cite.SnijdersEA07) >>
->> endobj
-404 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [218.19 186.883 281.536 198.838]
-/A << /S /GoTo /D (cite.SnijdersEA10a) >>
->> endobj
-405 0 obj <<
-/Type /Annot
-/Subtype /Link
-/Border[0 0 0]/H/I/C[0 1 0]
-/Rect [287.348 186.883 309.266 198.838]
-/A << /S /GoTo /D (cite.SnijdersEA10a) >>
->> endobj
-409 0 obj <<
-/D [407 0 R /XYZ 88.008 752.957 null]
->> endobj
-410 0 obj <<
-/D [407 0 R /XYZ 89.008 715.095 null]
->> endobj
-406 0 obj <<
-/Font << /F17 411 0 R /F18 412 0 R /F40 413 0 R /F41 414 0 R /F42 415 0 R /F8 416 0 R >>
-/XObject << /Fm1 398 0 R >>
-/ProcSet [ /PDF /Text ]
->> endobj
-465 0 obj <<
+203 0 obj <<
+/Type /ObjStm
+/N 100
+/First 869
+/Length 1637      
+/Filter /FlateDecode
+>>
+stream
+xڝ—ÛnÛ8†ïýs·-ÐÄIŠ¢@’6E€¦-š»@·ŒÄ8ÜÈ¢—’rxûýG[é6¶S 1)Šü83ÿð 
+H1).Šca at aÀeH¡ŠP*
+S.ñ/Ê”DÂeFR¡‚d¢fBH’?ƒ&¸LHqŠ3”!©,ìúQ¤¸=¥(å~ÅÚ• 8‹gBIJ¸ŸŠ)‰1N%”†’DPª`CR =R”Iô‹"ÊR~ŸÂþ®c†Š@ÏX°Gr&bI!šÐ£"TTxö^w.&p[0>†"Aç$B%ã
+ÈR‚œ€,OAV!Ș8T
+Ö¤ +•‚ f Gü
+·QÂ- Ç!·€s2ctÈI‘„•aÄ3€œÆ
+- g¿9ƒ+’•Ê “Ì
+D€
+<	DÉžiˆ
+üY"Èÿ „‚™„`‚ՐeöRB2Á0	Í FIÎIVR±äM(h!¡›PiŠ
+Èâ,¡œˆâl&!ˆn™”Šcͨ‡cRȇs…£ŸÂx(R8'¡ `‰%ÌiŠáPPd6Ãm‘A"É™š!l
+"Xà@A€!ùuÀÀ¤
+žØ7–[BAÆøI8ì”H©Yç$Ë-¡ üGŸ”ä8CÉ©-¡ |K»<—œÔ
+¼gSXedì	¯žXªÙ›74¿ ù÷ÍÑü½¨ÛKþ3yc]uªÃð%½};{ÑUéÔÞÛjA+íõÒ4Æ×/÷ ˆ
+AÐQÛ¸¥nlNW=Ë]='78I'®*,¿Ò%骠¶Ê'-¦n,Oæª}ÀjVôÕüÛZo
+ʯuµ05]y·¤)¼qÏ™m˜'éçH袁¹Úd¼w¿t|‘ö#Rúþ»Žb¡Bê²8hV†š=Šq  ‹Üy³ÿH9Ž”ôþ^/W¥yM®2µ-½ŽðŠš;÷¸µêz5f5Î씓l\D•ÎÛ²±ëüÙË`5•TA²[Czµ*mÞÉ÷šu¾5~aªÜÐÊ»ËÒ,wa£uJqjöêÊx†Ôtiš;c*²UaV?UCïÚÕ.n<rã5Ñ2tÍ;˜hló ìöU4ಖх]¶å–•1öÍ
+åp¤î¸6Ä3{ˆVPל¿©wÄH;Vm½Í¶=
+»ÛÓtQ©íaÎV+Â`tˆktî
+Sb…;››]¹Ç¦ƒ1üýýªtžç¾»¶ù5ȝ75ï¶Ê˶0»Œk^”}rn<š2,‚ÒÜ•A
+U—µÝ.I¸ñ'\¯¥.'‘¦Ò{SÄš"èÜ4ú`È›{ò¦~çgÄÄ(Áf=Ø“sN:ÝtY¸4ºêRèV{«9t˜’_ì¦tóL\øŸæ—à󧐓)ºƒ«ñºnÖ!Ý`‡è·|dÄ–Lmtê</VΏٸ]¼M´9ÖŸ†ô1·®l÷96yÔ”ðˆ¡Ë¶[Åt…õ½7MLh¢OJœ)ëÌÞêÕO(9AɍaUáî–¼ÿ>Ë.5©5ŒwÀœ
+dãš cs­o­ó|oxF´§z±b0¿ðGVýd×ïJL¢Îy>áíŠÕ’¾¬v[áwå±$vz}Gà}tÕÂ6maùhYò†¿;yä$«e¿Õ/ý¯Ò|e Ú”}_j46êýˆbB?muU¶ÝÞÿÛM3÷ì쌾àôGx–Øþ ¥®Z]n	꘾ŠÏËn³©]ë1]î~yLã†k
+>Ù>cnXΕ5=¸+ò—‡í8p¸·„1·¶Dø¯à$é²ä
+”÷ìüÚä7›Ý4¿Ñ‹m¦wç0¡£¢èÃv°=’µ–Iwh—TÝCº}×#+»»Œk›ƒÂ,¼1O¢qQÄÊ°÷‡G=õˆ>ZìãرO‡Ü®ù:öÙZßß›ü‰å½F÷¨c:¾6r·„Þ|_vd´/-X¸ÔLßÂ9é9'ø|ožÜ{6ÿÆ×ùùx6磫º&…ÛS at _gó¯¦O4áÛ²k:7…ÕÇîž¾sŸ(‹ESªÂÃ4û1ÉóÆ Ä@8ª*âw BnA)†R¥êK|×öÏÑPÆC™tå`‹ÿú|ùâOìëÙŸ«Y?¯çHýüiü.½;å÷pì¤ûòd
+endstream
+endobj
+468 0 obj <<
 /Length 1819      
 /Filter /FlateDecode
 >>
 stream
-xÚí[Kw›FÞûW°+Zˆ2/˜É.÷Ômíœ.Ò.Œ$Nxè(vþ}g˜@ §²DSËîÆ’`˜Çw_ß½ûÎÒñË3ß|þtwöã{Œ€=„èÜ-Ê<ߧNèc À¹Kœî»²˜!àÖ\T³¿î~>ó=`Ç÷ä`߃ˆ8BÎ9¼vs© óX 5¿ïÌ!ôBBõÔ`6g¸—¼à"ÊfsD‘›‹RäQÊe›•Ìnsäc¸ä©'#š yÞè\Íæ È-\§Eš7[‰{¥O*Êá`€uƒc»h¨ë´Xjª:5OÔìÞ§õJ­'§½i€„K}=ÍíÕůo·v;X²ÐóþÔÐÞLs,•ƒ@ìÌ5ªæž”%ð!tÏ£:’[GØ]Ì€[Ê«®_rõ%²ÚÓA¾ëÍæÄÙ˜±ýFàŒV\Ö|÷›RµmA#¢«BªX–i“¢BnT$ZfbSZåÕzÅõ—¥ˆÖ«4nìCþÜT\èái1ƒTº±ˆb3vS$öîò6p“rC÷~$ù  C DÜð0€¤
-10Rd­Ê c÷Ce À‡A±e®o^K"e±¾S
-ýù‹~jó0:–/=ÝÄJ¸9zœjhЀvÓiÐ^°Id
-¥ ¹7ÒVä,y)¸ð:J³~ƒ=É®&A‹Meˆ2h]س·F§üçhõ°Sp^§€<þ¦ž^Tuš÷ãª›™=…3DË`üÉ $Êsc¢
-”åB#wg!íÁ…v‘⫾qÎG$Ò“ˆèch‰ÀdÐZE¾•ƒ0qbšy§°ƒ-á <!£ßdxÈóÝÑN¤cý˜hßcpD³·)1ÛAŠ±§ÅŽ©œŠ;ìf@×ûäQÔŽ|‰>~q£Å
-T+/
-ˆ
-jÙÝûíˆX½*+C8îW¥!ÅÂØX•¥ËUc†™q]‹(O³42?’£A?ô˜Ì>÷¸ÜÃßUàO
-è`³ó=„‘ݵ„ñ19,6™…;.÷÷Eýᢊ´Oü&ø ô=Bö³6àùˆ=ð²)|¨Pà6ö‹-E5\’$UÚq#›Þ(:ã7‚/­¨s]*hRÇíg¯ÞO,°	o}þåëŒïP¿z0€[Ú·­tÌ;í¬b‘®>/JƒÓ²­	¡®&4„¢S¨{ìTXr h(õ|0ò'Ĉæ·M¥…Q*ÍEqŸ$5××Bj›ô%1O6‚È=E/4“R&ñD$5ØbN
-ÎyCR³:UF1@ºªøÈšÉ3J£¾_%¡‘™¨ð)ÜÖ|m2°…
-¦™Æ¾üܺ‘È8Á+)¦ª)¶÷âÇ›z7ÿ{èø/”<§ÇV‡	]HžëœR 2RÈ|ƒ±\¦_Zð_pE)Uøk*ÀÝaŒ¾‚Ï“¥3U	œY¹tÁ»+ž­{dÒ:®OÏÇuG _d3bWˆ>õaËMN&ó <j¼!жß>HvXý »oyÔ´ß6’9=	Á!t1°ÿ†tÿÍ–ùšØ¿–Tk$wƒ=uíájX¯vU¬7µ^+Qű­¥°LþÃ6Äì˜VbÔY°m¸kÕ¥
-I×
-Ÿ´eº?}€³±g‚”þߛۛ®÷$%ÓV'îTV¬®®ÞˆéSÒy­˜Ö½Ê¢T	µ¹#G‰ôaÐÏãÉÒ0±,­º#ßщe!ü®œLSVXÙ
-Âm-6q½‘)4M#.r™$úÈ_f$p£l3ÖêÁ¯0aŽ‹Û&ñùW¥bQ’ÆÒ¸Ô%¤H£z%&Á‹$$GŠNÂôq[©¾*I*“­¬ÄMý[‚	|zê®wQ ‰\nEazþQ¬<´É¿Œó•!u`Bµz¦ïÒ-³ÖÄÈ£&6ý[‡b‰'ÂÒnÎùZ‡¶"áVƒfÜ¿VÉ?íà'ÒéiþUômç:­º2N¢ÔtÈK%ÀÇ5_‡`ÈD‚±uwe®í¢ì—ÞcåòWQ±/)B/9Âî/ˆ`¢°k+9ïŒWâöFS/Û"“½ž×tþK1
-’ú¶ÂÐ$Û¡ÑÉöµj,A™˜÷‹«uó›Ç©ÊsãG^4†¸„‘{Ûõ•‰´™÷•5jQG]°“›SÊÕГИ,Nnñ¸®-"UGlôѦƒjÆÏ–|QžÆÕuˆéfYðy®KĉI‹^b)g󾿿ö²	S/Ò½Ÿû´£÷Ð\MÒhJh4÷4…îÖ_Rì­)œTSl.xÑ}¯ó3Ž¡uFæ¦DTU¦5§2d»þ½OºOCølàì½×|ùØÞƒ¡#ý¾G°ÿqÑòâîìo>öœŠ
+xÚí[IsÛ6¾ûWðVê –Ø ·4v<îÔm'v¦‡´†„,N¸h@*Nþ} )RNe™M½ôbI$ˆå{Û÷Þ£Cïƽó“Ð~þt}òã[Œ<€„#è]¯<ƃ0d
+q Pä]§ÞÿMU.ða>êÅ_×?Ÿ„‹°jp@D<©æ_{w® x#=è-!(afj°XrHüsQ
+ç‹%bÈÏÊU%‹¸ÉÔ²íJv·Þ‡%
+1ˆ|rß
+¨‚€í:/f‹% j—Y™í(ñ/ÌIe5Þ Œ0g~ôPÔn€E :š&+ouËF¤úöo³f­×SÓÀÁ4@ÁˆŒ¡™æêâì××;»-9
+Bà†ß÷l0Ó+å {Kƒª=G d	BýÓ¸‰ÕÖöWàWêª/Õ—B‰öôÒ(ôƒÅ’„Ïûs~ØÈ<€³È‰Ë™ïbÓª¶+"hEtQ*ËsccJTȏËÔÈLnËÒ(¢ºÚ¬…ùr#ãÍ:KZûP?·µfxV. S®A®âÄŽÝ–©»û‡º
+ü´Z@êßN$t”S€ˆOHÙE6ª0öß×
+|+Yææ¥Â!֐˜;•4Ÿ¿˜§¶_&Ç
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/rsiena -r 146

More information about the Rsiena-commits mailing list