[Rsiena-commits] r55 - in pkg/RSienaTest: . R doc man tests

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Thu Feb 11 16:14:58 CET 2010


Author: ripleyrm
Date: 2010-02-11 16:14:57 +0100 (Thu, 11 Feb 2010)
New Revision: 55

Modified:
   pkg/RSienaTest/DESCRIPTION
   pkg/RSienaTest/R/globals.r
   pkg/RSienaTest/R/siena07.r
   pkg/RSienaTest/changeLog
   pkg/RSienaTest/doc/s_man400.tex
   pkg/RSienaTest/man/siena07.Rd
   pkg/RSienaTest/tests/parallel.R
   pkg/RSienaTest/tests/parallel.Rout.save
Log:
New silent option for siena07, test output altered

Modified: pkg/RSienaTest/DESCRIPTION
===================================================================
--- pkg/RSienaTest/DESCRIPTION	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/DESCRIPTION	2010-02-11 15:14:57 UTC (rev 55)
@@ -4,7 +4,7 @@
 Version: 1.0.10
 Date: 2010-01-26
 Author: Various
-Depends: R (>= 2.7.0), xtable
+Depends: R (>= 2.9.0), xtable
 Imports: Matrix
 Suggests: tcltk, rlecuyer, snow, network, codetools
 SystemRequirements: GNU make, tcl/tk 8.5, Tktable

Modified: pkg/RSienaTest/R/globals.r
===================================================================
--- pkg/RSienaTest/R/globals.r	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/R/globals.r	2010-02-11 15:14:57 UTC (rev 55)
@@ -18,18 +18,20 @@
 cf <- NULL
 
 ##@Reportfun Reporting Part of global mechanism
-Reportfun<- function(x, verbose = FALSE)
+Reportfun<- function(x, verbose = FALSE, silent=FALSE)
 {
     x <- x
     beverbose <- verbose
+    besilent <- silent
     function(txt, dest, fill=FALSE, sep=" ", hdest,
              open=FALSE, close=FALSE,
-             type=c("a", "w"),  projname="Siena" , verbose=FALSE)
+             type=c("a", "w"),  projname="Siena" , verbose=FALSE, silent=FALSE)
     {
         if (open)
         {
             type <- match.arg(type)
             beverbose <<- verbose
+            besilent <<- silent
             if (type =='w')
             {
                 x$outf <<- file(paste(projname, ".out", sep=""), open="w")
@@ -48,7 +50,10 @@
         {
             if (missing(dest) && missing(hdest))
             {
-                cat(txt, fill = fill, sep = sep)
+                if (!besilent)
+                {
+                    cat(txt, fill = fill, sep = sep)
+                }
             }
             else
             {
@@ -87,8 +92,9 @@
 }
 
 ##@Report Globals
-Report <- local({verbose <-  NULL;
-                 Reportfun(list(outf=outf, lf=lf, cf=cf, bof=bof), verbose)})
+Report <- local({verbose <-  NULL; silent <- NULL;
+                 Reportfun(list(outf=outf, lf=lf, cf=cf, bof=bof), verbose,
+                           silent)})
 ##@UserInterrupt Siena07/GlobalFunctions Global (within siena07)
 UserInterrupt <- local({A <-  FALSE;function(x){if (!missing(x))A<<-x;A}})
 ##@EarlyEndPhase2 siena07/GlobalFunctions

Modified: pkg/RSienaTest/R/siena07.r
===================================================================
--- pkg/RSienaTest/R/siena07.r	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/R/siena07.r	2010-02-11 15:14:57 UTC (rev 55)
@@ -11,8 +11,8 @@
 ## ****************************************************************************/
 
 ##@siena07 siena07
-siena07<- function(x, batch = FALSE, verbose = FALSE, useCluster = FALSE,
-                   nbrNodes = 2, initC=FALSE,
+siena07<- function(x, batch = FALSE, verbose = FALSE, silent=FALSE,
+                   useCluster = FALSE, nbrNodes = 2, initC=FALSE,
                    clusterString=rep("localhost", nbrNodes), tt=NULL,
                    parallelTesting=FALSE, ...)
 {
@@ -81,7 +81,7 @@
     is.batch(batch)
 
     ## open the output file
-    Report(open=TRUE, projname=x$projname, verbose=verbose)
+    Report(open=TRUE, projname=x$projname, verbose=verbose, silent=silent)
     InitReports(seed, newseed)
 
     ## reset the globals for interrupts

Modified: pkg/RSienaTest/changeLog
===================================================================
--- pkg/RSienaTest/changeLog	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/changeLog	2010-02-11 15:14:57 UTC (rev 55)
@@ -1,3 +1,10 @@
+2010-02-11 R-forge revision 55 (cf revision 52)
+
+	* R/globals.r, R/siena07.r, man/siena07.Rd: 
+	new silent option with no output.
+	* tests/parallel.R, tests/parallel.Rout.save: suppress progress
+	message output and include prints of results.
+	
 2010-02-11 R-forge revision 54
 
 	* R/print07Report.r: source formatting

Modified: pkg/RSienaTest/doc/s_man400.tex
===================================================================
--- pkg/RSienaTest/doc/s_man400.tex	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/doc/s_man400.tex	2010-02-11 15:14:57 UTC (rev 55)
@@ -6799,6 +6799,8 @@
 (Programmers should consult the changeLog file on CRAN or in the R-forge
 repository.)
 \begin{itemize}
+\item 2010-02-11 R-forge revision 55 (RSienaTest only)
+New silent option for siena07.
 \item 2010-02-11 R-forge revision 54 (RSienaTest only)
 Fix to covariate behavior effect bug. 
 \item 2010-02-11 R-forge revision 53

Modified: pkg/RSienaTest/man/siena07.Rd
===================================================================
--- pkg/RSienaTest/man/siena07.Rd	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/man/siena07.Rd	2010-02-11 15:14:57 UTC (rev 55)
@@ -9,7 +9,7 @@
  data for the model must be passed in using named arguments as the \code{...}.
 (See examples)}
 \usage{
-siena07(x, batch=FALSE, verbose=FALSE, useCluster=FALSE,
+siena07(x, batch=FALSE, verbose=FALSE, silent=FALSE, useCluster=FALSE,
 nbrNodes=2, initC=FALSE, clusterString=rep("localhost", nbrNodes),
 tt=NULL, parallelTesting=FALSE, ...)
 }
@@ -18,6 +18,8 @@
   \item{batch}{ Desired interface: 'batch' is a small amount of printout
 	to the  console}
   \item{verbose}{Produces various output to the console if TRUE}
+  \item{silent}{Produces no output to the console if TRUE, even if batch
+  mode}
   \item{useCluster}{Boolean: whether to use a cluster of processes}
   \item{nbrNodes}{Number of processes to use if useCluster is TRUE}
   \item{initC}{Boolean: set to TRUE if the simulation will use C

Modified: pkg/RSienaTest/tests/parallel.R
===================================================================
--- pkg/RSienaTest/tests/parallel.R	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/tests/parallel.R	2010-02-11 15:14:57 UTC (rev 55)
@@ -8,13 +8,17 @@
 mymodel<- model.create(findiff=TRUE, fn = simstats0c, projname='test3',
                        cond=FALSE, nsub=2, n3=100)
 print('test3')
-ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, silent=TRUE)#,dll='../siena/src/RSiena.dll')
+ans
 ##test4
 mymodel$projname <- 'test4'
 mymodel$cconditional <- TRUE
 mymodel$condvarno<- 1
 print('test4')
-ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE,
+              parallelTesting=TRUE, silent=TRUE)
+##, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans
 ##test7
 mynet1 <- sienaNet(array(c(tmp3,tmp4),dim=c(32,32,2)))
 mydata <- sienaDataCreate(mynet1)
@@ -22,13 +26,19 @@
 mymodel<- model.create(fn = simstats0c, projname='test7', nsub=2, n3=100,
                        cond=FALSE)
 print('test7')
-ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE,
+              parallelTesting=TRUE, silent=TRUE)
+##, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans
 ##test8
 mymodel$projname <- 'test8'
 mymodel$cconditional <- TRUE
 mymodel$condvarno<- 1
 print('test8')
-ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans <- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE,
+              parallelTesting=TRUE, silent=TRUE)
+##, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+ans
 ##test9
 
 mynet1 <- sienaNet(array(c(s501, s502, s503), dim=c(50, 50, 3)))
@@ -41,7 +51,10 @@
 mymodel$projname <- 'test10'
 mymodel$cconditional <- TRUE
 mymodel$condvarno<- 1
-ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)
+ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE,
+               parallelTesting=TRUE, silent=TRUE)
+##, verbose=TRUE)
+ans
 ##test11
 print('test11')
 data501 <- sienaDataCreateFromSession("s50.csv", modelName="s50")
@@ -50,5 +63,7 @@
 
 model501e <- model.create( projname="s50e", cond=FALSE, nsub=2, n3=100 )
 ans501e <- siena07(model501e, data=data501e$mydata, effects=data501e$myeff,
-                   parallelTesting=TRUE, batch=TRUE, verbose=TRUE)
+                   parallelTesting=TRUE, batch=TRUE, silent=TRUE)
+##, verbose=TRUE)
+ans501e
 ## compare with outputs in parallelchecked/

Modified: pkg/RSienaTest/tests/parallel.Rout.save
===================================================================
--- pkg/RSienaTest/tests/parallel.Rout.save	2010-02-11 14:31:32 UTC (rev 54)
+++ pkg/RSienaTest/tests/parallel.Rout.save	2010-02-11 15:14:57 UTC (rev 55)
@@ -17,340 +17,51 @@
 
 > library(RSienaTest)
 Loading required package: xtable
-> print(packageDescription("RSienaTest",fields="Repository/R-Forge/Revision"))
-[1] NA
-> 
-> ##test3
-> mynet1 <- sienaNet(array(c(tmp3, tmp4),dim=c(32, 32, 2)))
-> mydata <- sienaDataCreate(mynet1)
-> myeff<- getEffects(mydata)
-> mymodel<- model.create(findiff=TRUE, fn = simstats0c, projname='test3',
-+                        cond=FALSE, nsub=2, n3=100)
-> print('test3')
-[1] "test3"
-> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
-
-Stochastic approximation algorithm.
-Initial value for gain parameter = 0.2.
-Start of the algorithm.
-Target function values are 
-  1.    51.0000   2.   129.0000   3.    58.0000
-
-Start phase 0 
-theta:  4.81 -0.56  0.00 
-Current parameter values:
- 4.8094118 -0.5603907  0.0000000
-
-Start phase 1 
-Phase 1 Iteration 1 Progress: 0%
-Phase 1 Iteration 2 Progress: 1%
-Phase 1 Iteration 3 Progress: 1%
-Phase 1 Iteration 4 Progress: 2%
-Phase 1 Iteration 5 Progress: 2%
-Phase 1 Iteration 6 Progress: 3%
-Phase 1 Iteration 7 Progress: 3%
-Phase 1 Iteration 8 Progress: 3%
-Phase 1 Iteration 9 Progress: 4%
-Phase 1 Iteration 10 Progress: 4%
-Phase 1 Iteration 11 Progress: 5%
-Phase 1 Iteration 12 Progress: 5%
-Phase 1 Iteration 13 Progress: 5%
-Phase 1 Iteration 14 Progress: 6%
-Phase 1 Iteration 15 Progress: 6%
-Phase 1 Iteration 16 Progress: 7%
-Time per iteration in phase 1  = 0.02533 
-Average deviations NR generated statistics and targets
-after phase 1:
-      32.437500
-       8.687500
-     -25.875000
-
-Diagonal values of derivative matrix :
- 18.1935  90.6250  31.2500
-dfra :
-18.193493  4.375000  1.875000
- 4.938234 90.625000 34.375000
--3.638699 50.000000 31.250000
+> print(packageDescription("RSienaTest",fields="Repository/R-Forge/Revision"))
+[1] NA
+> 
+> ##test3
+> mynet1 <- sienaNet(array(c(tmp3, tmp4),dim=c(32, 32, 2)))
+> mydata <- sienaDataCreate(mynet1)
+> myeff<- getEffects(mydata)
+> mymodel<- model.create(findiff=TRUE, fn = simstats0c, projname='test3',
++                        cond=FALSE, nsub=2, n3=100)
+> print('test3')
+[1] "test3"
+> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, silent=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans
+Estimates, standard errors and t-statistics for convergence
 
-inverse of dfra :
- 0.0553503550 -0.0021363295 -0.0009710589
--0.0138912725  0.0286063298 -0.0306334864
- 0.0286709404 -0.0460188784  0.0809005098
+                                      Estimate   Standard   t statistic 
+                                                   Error                
+  1. rate basic rate parameter mynet1  3.0264  ( 0.5202   ) -0.0780     
+  2. eval outdegree (density)         -1.1343  ( 0.1653   )  0.1078     
+  3. eval reciprocity                  1.7921  ( 0.2370   ) -0.0392     
 
-Full Quasi-Newton-Raphson step after phase 1:
-1.    -1.801994
-2.    -0.590561
-3.     1.563076 
-This step is multiplied by the factor  0.10000.
-Phase 1 achieved after  16  iterations.
-theta:  4.629 -0.619  0.156 
-Current parameter values:
- 4.6292124 -0.6194468  0.1563076
-
-Phase 2 has 2 subphases.
-Each subphase can be repeated up to 4 times
-
-Start phase 2.1
-Phase 2 Subphase 1 Iteration 1 Progress: 7%
-Phase 2 Subphase 1 Iteration 2 Progress: 7%
-theta  4.244 -0.648  0.310 
-ac 1.46 1.30 1.00 
-Phase 2 Subphase 1 Iteration 3 Progress: 7%
-Phase 2 Subphase 1 Iteration 4 Progress: 7%
-theta  3.772 -0.694  0.540 
-ac 1.459 1.480 0.836 
-Phase 2 Subphase 1 Iteration 5 Progress: 7%
-Phase 2 Subphase 1 Iteration 6 Progress: 7%
-theta  3.42 -0.76  0.72 
-ac 1.25 1.94 0.65 
-Phase 2 Subphase 1 Iteration 7 Progress: 7%
-Phase 2 Subphase 1 Iteration 8 Progress: 8%
-theta  3.244 -0.783  0.912 
-ac 0.799 0.794 0.653 
-Phase 2 Subphase 1 Iteration 9 Progress: 8%
-Phase 2 Subphase 1 Iteration 10 Progress: 8%
-theta  2.969 -0.838  1.040 
-ac 0.792 0.780 0.653 
-Warning: an autocorrelation is positive at the end of this subphase.
-Autocorrelations:
-0.1206780
-0.1117977
-0.1982289
-
-Time per iteration in phase 2.1 = 0.004089
-theta  3.10 -1.09  1.67 
-ac 0.121 0.112 0.198 
-Phase 2.1 ended after 225 iterations.
-Warning. Autocorrelation criterion not satisfied.
-theta:  3.10 -1.09  1.67 
-Current parameter values:
- 3.102896 -1.092006  1.668237
-
-Start phase 2.2
-Phase 2 Subphase 2 Iteration 1 Progress: 30%
-Phase 2 Subphase 2 Iteration 2 Progress: 31%
-Phase 2 Subphase 2 Iteration 3 Progress: 31%
-Phase 2 Subphase 2 Iteration 4 Progress: 31%
-Phase 2 Subphase 2 Iteration 5 Progress: 31%
-Phase 2 Subphase 2 Iteration 6 Progress: 31%
-Phase 2 Subphase 2 Iteration 7 Progress: 31%
-Phase 2 Subphase 2 Iteration 8 Progress: 31%
-Phase 2 Subphase 2 Iteration 9 Progress: 31%
-Phase 2 Subphase 2 Iteration 10 Progress: 31%
-Time per iteration in phase 2.2 = 0.003992
-theta  3.03 -1.13  1.79 
-ac  0.0471 -0.0488  0.0117 
-Phase 2.2 ended after 263 iterations.
-theta:  3.03 -1.13  1.79 
-Current parameter values:
- 3.026403 -1.134321  1.792116
-
-Start phase 3 
-Simulated values, phase 3.
-Time per iteration in phase 3   =  0.0153 
-dfrac :
-12.246820 11.600000  5.800000
- 3.555528 44.000000 10.800000
- 2.287182 16.200000 23.800000
-
-inverse of dfra :
- 0.089575512 -0.018702986 -0.013342257
--0.006153542  0.028570901 -0.011465344
--0.004419669 -0.017650062  0.051103141
-
-A full Quasi-Newton-Raphson step after phase 3
-would add the following numbers to the parameters, yielding the following results:
-         change     new value 
-   1.     0.054275    3.080679
-   2.    -0.027190   -1.161511
-   3.     0.022535    1.814651 
-
-unconditional moment estimation.
-Information for convergence diagnosis.
-Averages, standard deviations, and t-ratios for deviations from targets:
-  1.  -0.4800   6.1521  -0.0780
-  2.   0.7600   7.0526   0.1078
-  3.  -0.2200   5.6131  -0.0392
-
 Total of 604 iteration steps.
 
- at 3
-Estimates and standard errors
-                             
- 1. rate:  basic rate parameter mynet1                   3.0264  (   0.5202)
- 2. eval:  outdegree (density)                          -1.1343  (   0.1653)
- 3. eval:  reciprocity                                   1.7921  (   0.2370)
-
-Derivative matrix of expected statistics X by parameters:
-
- 12.246820 11.600000  5.800000
- 3.555528 44.000000 10.800000
- 2.287182 16.200000 23.800000
-
-Covariance matrix of X (correlations below the diagonal):
-    37.848     14.469      7.914
-     0.333     49.740     22.735
-     0.229      0.574     31.507
-
-
 > ##test4
 > mymodel$projname <- 'test4'
 > mymodel$cconditional <- TRUE
 > mymodel$condvarno<- 1
 > print('test4')
 [1] "test4"
-> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE,
++               parallelTesting=TRUE, silent=TRUE)
+> ##, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans
+Estimates, standard errors and t-statistics for convergence
 
-Stochastic approximation algorithm.
-Initial value for gain parameter = 0.2.
-Start of the algorithm.
-Target function values are 
-  1.   129.0000   2.    58.0000
-
-Start phase 0 
-theta: -0.56  0.00 
-Current parameter values:
--0.5603907  0.0000000
-
-Start phase 1 
-Phase 1 Iteration 1 Progress: 0%
-Phase 1 Iteration 2 Progress: 1%
-Phase 1 Iteration 3 Progress: 1%
-Phase 1 Iteration 4 Progress: 1%
-Phase 1 Iteration 5 Progress: 2%
-Phase 1 Iteration 6 Progress: 2%
-Phase 1 Iteration 7 Progress: 3%
-Phase 1 Iteration 8 Progress: 3%
-Phase 1 Iteration 9 Progress: 3%
-Phase 1 Iteration 10 Progress: 4%
-Phase 1 Iteration 11 Progress: 4%
-Phase 1 Iteration 12 Progress: 4%
-Phase 1 Iteration 13 Progress: 5%
-Time per iteration in phase 1  = 0.0100 
-Average deviations NR generated statistics and targets
-after phase 1:
-       2.461538
-     -16.923077
-
-Diagonal values of derivative matrix :
- 47.6923  23.0769
-dfra :
-47.692308 29.230769
- 3.076923 23.076923
-
-inverse of dfra :
- 0.022833724 -0.028922717
--0.003044496  0.047189696
-
-Full Quasi-Newton-Raphson step after phase 1:
-1.    -0.545667
-2.     0.806089 
-This step is multiplied by the factor  0.10000.
-Phase 1 achieved after  13  iterations.
-theta: -0.6150  0.0806 
-Current parameter values:
--0.6149574  0.0806089
-
-Phase 2 has 2 subphases.
-Each subphase can be repeated up to 4 times
-
-Start phase 2.1
-Phase 2 Subphase 1 Iteration 1 Progress: 5%
-Phase 2 Subphase 1 Iteration 2 Progress: 5%
-theta -0.581  0.289 
-ac -2  1 
-Phase 2 Subphase 1 Iteration 3 Progress: 5%
-Phase 2 Subphase 1 Iteration 4 Progress: 5%
-theta -0.665  0.514 
-ac 3.333 0.882 
-Phase 2 Subphase 1 Iteration 5 Progress: 5%
-Phase 2 Subphase 1 Iteration 6 Progress: 6%
-theta -0.732  0.705 
-ac 2.500 0.812 
-Phase 2 Subphase 1 Iteration 7 Progress: 6%
-Phase 2 Subphase 1 Iteration 8 Progress: 6%
-theta -0.732  0.982 
-ac 2.526 0.825 
-Phase 2 Subphase 1 Iteration 9 Progress: 6%
-Phase 2 Subphase 1 Iteration 10 Progress: 6%
-theta -0.732  1.121 
-ac 2.350 0.802 
-Warning: an autocorrelation is positive at the end of this subphase.
-Autocorrelations:
-0.02784048
-0.20161290
-
-Time per iteration in phase 2.1 = 0.004099
-theta -1.11  1.71 
-ac 0.0278 0.2016 
-Phase 2.1 ended after 222 iterations.
-Warning. Autocorrelation criterion not satisfied.
-theta: -1.11  1.71 
-Current parameter values:
--1.108818  1.709165
-
-Start phase 2.2
-Phase 2 Subphase 2 Iteration 1 Progress: 32%
-Phase 2 Subphase 2 Iteration 2 Progress: 32%
-Phase 2 Subphase 2 Iteration 3 Progress: 32%
-Phase 2 Subphase 2 Iteration 4 Progress: 32%
-Phase 2 Subphase 2 Iteration 5 Progress: 33%
-Phase 2 Subphase 2 Iteration 6 Progress: 33%
-Phase 2 Subphase 2 Iteration 7 Progress: 33%
-Phase 2 Subphase 2 Iteration 8 Progress: 33%
-Phase 2 Subphase 2 Iteration 9 Progress: 33%
-Phase 2 Subphase 2 Iteration 10 Progress: 33%
-Time per iteration in phase 2.2 = 0.003818
-theta -1.10  1.70 
-ac -0.072 -0.128 
-Phase 2.2 ended after 55 iterations.
-theta: -1.10  1.70 
-Current parameter values:
--1.095189  1.700653
-
-Start phase 3 
-Simulated values, phase 3.
-Time per iteration in phase 3   =  0.0114 
-dfrac :
-41.0 14.0
-22.2 22.8
-
-inverse of dfra :
- 0.03653846 -0.02243590
--0.03557692  0.06570513
-
-A full Quasi-Newton-Raphson step after phase 3
-would add the following numbers to the parameters, yielding the following results:
-         change     new value 
-   1.    -0.057269   -1.152458
-   2.     0.066288    1.766942 
-
-conditional moment estimation.
-Information for convergence diagnosis.
-Averages, standard deviations, and t-ratios for deviations from targets:
-  1.   1.4200   6.4089   0.2216
-  2.  -0.2400   5.7228  -0.0419
-
-Total of 390 iteration steps.
-
- at 3
-Estimates and standard errors
+                              Estimate   Standard   t statistic 
+                                           Error                
                              
 Rate parameters:
- 0. Rate parameter                            3.0428  (   0.5235)
- 1. eval:  outdegree (density)                          -1.0952  (   0.1923)
- 2. eval:  reciprocity                                   1.7007  (   0.3089)
+  0       Rate parameter       3.0428  ( 0.5235   )             
+  1. eval outdegree (density) -1.0952  ( 0.1923   )  0.2216     
+  2. eval reciprocity          1.7007  ( 0.3089   ) -0.0419     
 
-Derivative matrix of expected statistics X by parameters:
+Total of 390 iteration steps.
 
- 41.0 14.0
-22.2 22.8
-
-Covariance matrix of X (correlations below the diagonal):
-    41.074     20.950
-     0.571     32.750
-
-
 > ##test7
 > mynet1 <- sienaNet(array(c(tmp3,tmp4),dim=c(32,32,2)))
 > mydata <- sienaDataCreate(mynet1)
@@ -359,307 +70,42 @@
 +                        cond=FALSE)
 > print('test7')
 [1] "test7"
-> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE,
++               parallelTesting=TRUE, silent=TRUE)
+> ##, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans
+Estimates, standard errors and t-statistics for convergence
 
-Stochastic approximation algorithm.
-Initial value for gain parameter = 0.2.
-Start of the algorithm.
-Target function values are 
-  1.    51.0000   2.   129.0000   3.    58.0000
+                                      Estimate   Standard   t statistic 
+                                                   Error                
+  1. rate basic rate parameter mynet1  3.1122  ( 0.4077   ) 0.1685      
+  2. eval outdegree (density)         -1.1288  ( 0.2181   ) 0.1968      
+  3. eval reciprocity                  1.7487  ( 0.4069   ) 0.1410      
 
-Start phase 0 
-theta:  4.81 -0.56  0.00 
-Current parameter values:
- 4.8094118 -0.5603907  0.0000000
-
-Start phase 1 
-Phase 1 Iteration 1 Progress: 0%
-Phase 1 Iteration 2 Progress: 0%
-Phase 1 Iteration 3 Progress: 0%
-Phase 1 Iteration 4 Progress: 1%
-Phase 1 Iteration 5 Progress: 1%
-Phase 1 Iteration 10 Progress: 2%
-Phase 1 Iteration 15 Progress: 2%
-Time per iteration in phase 1  = 0.005333 
-Average deviations NR generated statistics and targets
-after phase 1:
-      32.437500
-       8.687500
-     -25.875000
-
-Diagonal values of derivative matrix :
- 13.8076  64.3695  10.7603
-dfra :
-13.807562 25.392227  8.668270
- 3.619206 64.369544  4.601454
--3.209852 -2.343346 10.760317
-
-inverse of dfra :
- 0.069880120 -0.029161393 -0.043823515
--0.005336113  0.017523947 -0.003195145
- 0.019683480 -0.004882671  0.079165481
-
-Full Quasi-Newton-Raphson step after phase 1:
-1.   -3.1473302
-2.   -0.0618235
-3.    1.4523421 
-This step is multiplied by the factor  0.10000.
-Phase 1 achieved after  16  iterations.
-theta:  4.495 -0.567  0.145 
-Current parameter values:
- 4.4946787 -0.5665730  0.1452342
-
-Phase 2 has 2 subphases.
-Each subphase can be repeated up to 4 times
-
-Start phase 2.1
-Phase 2 Subphase 1 Iteration 1 Progress: 10%
-Phase 2 Subphase 1 Iteration 2 Progress: 10%
-theta  3.988 -0.601  0.591 
-ac 1.75 1.38 1.20 
-Phase 2 Subphase 1 Iteration 3 Progress: 10%
-Phase 2 Subphase 1 Iteration 4 Progress: 10%
-theta  3.466 -0.669  1.186 
-ac 1.79 1.03 1.20 
-Phase 2 Subphase 1 Iteration 5 Progress: 11%
-Phase 2 Subphase 1 Iteration 6 Progress: 11%
-theta  3.278 -0.753  1.112 
-ac 1.431 1.069 0.634 
-Phase 2 Subphase 1 Iteration 7 Progress: 11%
-Phase 2 Subphase 1 Iteration 8 Progress: 11%
-theta  2.988 -0.859  1.186 
-ac 1.18 1.64 0.69 
-Phase 2 Subphase 1 Iteration 9 Progress: 11%
-Phase 2 Subphase 1 Iteration 10 Progress: 11%
-theta  2.90 -0.92  1.19 
-ac 1.182 1.643 0.689 
-Warning: an autocorrelation is positive at the end of this subphase.
-Autocorrelations:
- 0.14682200
- 0.03195180
--0.00410509
-
-Time per iteration in phase 2.1 = 0.004089
-theta  3.12 -1.11  1.73 
-ac  0.14682  0.03195 -0.00411 
-Phase 2.1 ended after 225 iterations.
-Warning. Autocorrelation criterion not satisfied.
-theta:  3.12 -1.11  1.73 
-Current parameter values:
- 3.118108 -1.109539  1.728403
-
-Start phase 2.2
-Phase 2 Subphase 2 Iteration 1 Progress: 44%
-Phase 2 Subphase 2 Iteration 2 Progress: 45%
-Phase 2 Subphase 2 Iteration 3 Progress: 45%
-Phase 2 Subphase 2 Iteration 4 Progress: 45%
-Phase 2 Subphase 2 Iteration 5 Progress: 45%
-Phase 2 Subphase 2 Iteration 6 Progress: 45%
-Phase 2 Subphase 2 Iteration 7 Progress: 45%
-Phase 2 Subphase 2 Iteration 8 Progress: 46%
-Phase 2 Subphase 2 Iteration 9 Progress: 46%
-Phase 2 Subphase 2 Iteration 10 Progress: 46%
-Time per iteration in phase 2.2 = 0.004286
-theta  3.11 -1.13  1.75 
-ac -0.112 -0.219 -0.157 
-Phase 2.2 ended after 63 iterations.
-theta:  3.11 -1.13  1.75 
-Current parameter values:
- 3.112224 -1.128763  1.748732
-
-Start phase 3 
-Simulated values, phase 3.
-Time per iteration in phase 3   =  0.0052 
-dfrac :
-18.4056484  3.7142613 -0.3794248
- 2.1526407 49.1035790 18.8351756
- 0.8324594 30.4016978 22.7488175
-
-inverse of dfra :
- 0.055061810 -0.009712224  0.008959730
--0.003366908  0.042378759 -0.035144194
- 0.002484657 -0.056279901  0.090597437
-
-A full Quasi-Newton-Raphson step after phase 3
-would add the following numbers to the parameters, yielding the following results:
-         change     new value 
-   1.    -0.063242    3.048982
-   2.    -0.023482   -1.152245
-   3.    -0.003230    1.745503 
-
-unconditional moment estimation.
-Information for convergence diagnosis.
-Averages, standard deviations, and t-ratios for deviations from targets:
-  1.   1.2500   7.4201   0.1685
-  2.   1.3500   6.8584   0.1968
-  3.   0.8400   5.9573   0.1410
-
 Total of 404 iteration steps.
 
- at 3
-Estimates and standard errors
-                             
- 1. rate:  basic rate parameter mynet1                   3.1122  (   0.4077)
- 2. eval:  outdegree (density)                          -1.1288  (   0.2181)
- 3. eval:  reciprocity                                   1.7487  (   0.4069)
-
-Derivative matrix of expected statistics X by parameters:
-
- 18.4056484  3.7142613 -0.3794248
- 2.1526407 49.1035790 18.8351756
- 0.8324594 30.4016978 22.7488175
-
-Covariance matrix of X (correlations below the diagonal):
-    55.058      7.194      4.475
-     0.141     47.038     26.976
-     0.101      0.660     35.489
-
-
 > ##test8
 > mymodel$projname <- 'test8'
 > mymodel$cconditional <- TRUE
 > mymodel$condvarno<- 1
 > print('test8')
 [1] "test8"
-> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans <- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE,
++               parallelTesting=TRUE, silent=TRUE)
+> ##, verbose=TRUE)#,dll='../siena/src/RSiena.dll')
+> ans
+Estimates, standard errors and t-statistics for convergence
 
-Stochastic approximation algorithm.
-Initial value for gain parameter = 0.2.
-Start of the algorithm.
-Target function values are 
-  1.   129.0000   2.    58.0000
-
-Start phase 0 
-theta: -0.56  0.00 
-Current parameter values:
--0.5603907  0.0000000
-
-Start phase 1 
-Phase 1 Iteration 1 Progress: 0%
-Phase 1 Iteration 2 Progress: 0%
-Phase 1 Iteration 3 Progress: 0%
-Phase 1 Iteration 4 Progress: 1%
-Phase 1 Iteration 5 Progress: 1%
-Phase 1 Iteration 10 Progress: 2%
-Time per iteration in phase 1  = 0.004167 
-Average deviations NR generated statistics and targets
-after phase 1:
-       2.461538
-     -18.461538
-
-Diagonal values of derivative matrix :
- 37.9097  17.1918
-dfra :
-37.90974 14.52753
-28.35958 17.19178
-
-inverse of dfra :
- 0.07170969 -0.06059666
--0.11829240  0.15812767
-
-Full Quasi-Newton-Raphson step after phase 1:
-1.    -1.295224
-2.     3.210461 
-This step is multiplied by the factor  0.10000.
-Phase 1 achieved after  13  iterations.
-theta: -0.690  0.321 
-Current parameter values:
--0.6899131  0.3210461
-
-Phase 2 has 2 subphases.
-Each subphase can be repeated up to 4 times
-
-Start phase 2.1
-Phase 2 Subphase 1 Iteration 1 Progress: 6%
-Phase 2 Subphase 1 Iteration 2 Progress: 7%
-theta -0.679  0.577 
-ac -0.25  1.38 
-Phase 2 Subphase 1 Iteration 3 Progress: 7%
-Phase 2 Subphase 1 Iteration 4 Progress: 7%
-theta -0.785  0.763 
-ac -0.800  0.607 
-Phase 2 Subphase 1 Iteration 5 Progress: 7%
-Phase 2 Subphase 1 Iteration 6 Progress: 7%
-theta -0.817  1.135 
-ac 0.111 0.718 
-Phase 2 Subphase 1 Iteration 7 Progress: 7%
-Phase 2 Subphase 1 Iteration 8 Progress: 8%
-theta -0.87  1.25 
-ac 0.156 0.571 
-Phase 2 Subphase 1 Iteration 9 Progress: 8%
-Phase 2 Subphase 1 Iteration 10 Progress: 8%
-theta -0.922  1.368 
-ac 0.109 0.535 
-Time per iteration in phase 2.1 = 0.003936
-theta -1.11  1.66 
-ac -0.0414  0.0000 
-Phase 2.1 ended after 94 iterations.
-theta: -1.11  1.66 
-Current parameter values:
--1.109191  1.657303
-
-Start phase 2.2
-Phase 2 Subphase 2 Iteration 1 Progress: 43%
-Phase 2 Subphase 2 Iteration 2 Progress: 43%
-Phase 2 Subphase 2 Iteration 3 Progress: 43%
-Phase 2 Subphase 2 Iteration 4 Progress: 43%
-Phase 2 Subphase 2 Iteration 5 Progress: 43%
-Phase 2 Subphase 2 Iteration 6 Progress: 43%
-Phase 2 Subphase 2 Iteration 7 Progress: 44%
-Phase 2 Subphase 2 Iteration 8 Progress: 44%
-Phase 2 Subphase 2 Iteration 9 Progress: 44%
-Phase 2 Subphase 2 Iteration 10 Progress: 44%
-Time per iteration in phase 2.2 = 0.004032
-theta -1.12  1.74 
-ac -0.0299 -0.3052 
-Phase 2.2 ended after 62 iterations.
-theta: -1.12  1.74 
-Current parameter values:
--1.122423  1.739476
-
-Start phase 3 
-Simulated values, phase 3.
-Time per iteration in phase 3   =  0.0041 
-dfrac :
-33.189028  8.787036
-15.949957 19.294151
-
-inverse of dfra :
- 0.03857277 -0.01756700
--0.03188708  0.06635135
-
-A full Quasi-Newton-Raphson step after phase 3
-would add the following numbers to the parameters, yielding the following results:
-         change     new value 
-   1.    -0.013756   -1.136179
-   2.     0.026921    1.766396 
-
-conditional moment estimation.
-Information for convergence diagnosis.
-Averages, standard deviations, and t-ratios for deviations from targets:
-  1.   0.2200   6.3494   0.0346
-  2.  -0.3000   5.4781  -0.0548
-
-Total of 269 iteration steps.
-
- at 3
-Estimates and standard errors
+                              Estimate   Standard   t statistic 
+                                           Error                
                              
 Rate parameters:
- 0. Rate parameter                            3.1368  (   0.4867)
- 1. eval:  outdegree (density)                          -1.1224  (   0.2040)
- 2. eval:  reciprocity                                   1.7395  (   0.2947)
+  0       Rate parameter       3.1368  ( 0.4867   )             
+  1. eval outdegree (density) -1.1224  ( 0.2040   )  0.0346     
+  2. eval reciprocity          1.7395  ( 0.2947   ) -0.0548     
 
-Derivative matrix of expected statistics X by parameters:
+Total of 269 iteration steps.
 
- 33.189028  8.787036
-15.949957 19.294151
-
-Covariance matrix of X (correlations below the diagonal):
-    40.315     20.390
-     0.586     30.010
-
-
 > ##test9
 > 
 > mynet1 <- sienaNet(array(c(s501, s502, s503), dim=c(50, 50, 3)))
@@ -673,197 +119,32 @@
 > mymodel$projname <- 'test10'
 > mymodel$cconditional <- TRUE
 > mymodel$condvarno<- 1
-> ans<- siena07(mymodel, data=mydata, effects=myeff,  batch=TRUE, parallelTesting=TRUE, verbose=TRUE)
+> ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE,
++                parallelTesting=TRUE, silent=TRUE)
+> ##, verbose=TRUE)
+> ans
+Estimates, standard errors and t-statistics for convergence
 
-Stochastic approximation algorithm.
-Initial value for gain parameter = 0.2.
-Start of the algorithm.
-Target function values are 
-  1.  238.00000   2.  160.00000   3.   27.00000   4.   33.00000   5.   11.66667 
-  6.  121.07111
-
-Start phase 0 
-theta: -1.468  0.000  0.150  0.196  0.347  0.000 
-Current parameter values:
--1.4677046  0.0000000  0.1502785  0.1962158  0.3469993  0.0000000
-
-Start phase 1 
-Phase 1 Iteration 1 Progress: 0%
-Phase 1 Iteration 2 Progress: 0%
-Phase 1 Iteration 3 Progress: 0%
-Phase 1 Iteration 4 Progress: 1%
-Phase 1 Iteration 5 Progress: 1%
-Phase 1 Iteration 10 Progress: 1%
-Phase 1 Iteration 15 Progress: 2%
-Phase 1 Iteration 20 Progress: 3%
-Phase 1 Iteration 25 Progress: 3%
-Time per iteration in phase 1  = 0.01125 
-Average deviations NR generated statistics and targets
-after phase 1:
-      11.760000
-    -109.520000
-     -14.240000
-     -18.040000
-     -15.400000
-      19.210667
-
-Diagonal values of derivative matrix :
-184.1470  41.2023 130.8936  56.9510  17.8468  65.4993
-dfra :
-184.1469860  33.7901540 -55.2718152 -87.6656728  -8.6492102  -0.8484742
- 71.5353970  41.2023497 -85.3876923 -15.8453356  -5.3931674   0.4452829
--10.4182899  -1.8666885 130.8936185   0.0000000  -1.2121271 -11.7894165
--17.1952963  -1.7312880   0.0000000  56.9510154  -0.9785957  -8.3938226
--20.3796807 -11.0092783  37.5315279  19.3423699  17.8467508  -7.0803547
--15.8582504   1.8407313 -23.1128153 -29.1206022   1.7265029  65.4993016
-
-inverse of dfra :
- 0.0097471595 -0.0067280929 -0.0008168317  0.0131062002  0.0031559329  0.0020457072
--0.0138770754  0.0371631474  0.0172862934 -0.0118096551  0.0048679310  0.0016917950
- 0.0009758352 -0.0001930769  0.0079895533  0.0020720409  0.0008953170  0.0018143342
- 0.0031700032 -0.0011771922  0.0005407109  0.0230843148  0.0021601393  0.0033381839
--0.0011193332  0.0154670271 -0.0066450197 -0.0157777957  0.0585582149  0.0029923843
- 0.0045331185 -0.0036725600  0.0025512730  0.0149152745  0.0003600641  0.0177605731
-
-Full Quasi-Newton-Raphson step after phase 1:
-1.   -0.6173812
-2.    4.3088786
-3.    0.0974626
-4.    0.2270728
-5.    2.1721665
-6.   -0.4857740 
-This step is multiplied by the factor  0.10000.
-Phase 1 achieved after  25  iterations.
-theta: -1.5294  0.4309  0.1600  0.2189  0.5642 -0.0486 
-Current parameter values:
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/rsiena -r 55


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