[Pomp-commits] r712 - in pkg/pompExamples: . tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Tue May 8 23:19:46 CEST 2012
Author: kingaa
Date: 2012-05-08 23:19:46 +0200 (Tue, 08 May 2012)
New Revision: 712
Modified:
pkg/pompExamples/DESCRIPTION
pkg/pompExamples/tests/pertussis.Rout.save
Log:
- bring unit tests up to date
Modified: pkg/pompExamples/DESCRIPTION
===================================================================
--- pkg/pompExamples/DESCRIPTION 2012-05-08 21:19:27 UTC (rev 711)
+++ pkg/pompExamples/DESCRIPTION 2012-05-08 21:19:46 UTC (rev 712)
@@ -1,12 +1,12 @@
Package: pompExamples
Type: Package
Title: Statistical inference for partially observed Markov processes
-Version: 0.20-3
-Date: 2012-05-08
+Version: 0.20-4
+Date: 2012-05-09
Author: NCEAS Working Group on Inference for Mechanistic Models: Aaron King, Steve Ellner, Bruce Kendall, Daniel C. Reuman, Matt Ferrari, Ed Ionides, Helen Wearing
Maintainer: Aaron A. King <kingaa at umich.edu>
Description: Inference methods for partially-observed Markov processes
-Depends: R(>= 2.14.2), stats, methods, graphics, pomp(>= 0.41-3)
+Depends: R(>= 2.14.2), stats, methods, graphics, pomp(>= 0.42-2)
License: GPL (>= 2)
LazyLoad: true
LazyData: false
Modified: pkg/pompExamples/tests/pertussis.Rout.save
===================================================================
--- pkg/pompExamples/tests/pertussis.Rout.save 2012-05-08 21:19:27 UTC (rev 711)
+++ pkg/pompExamples/tests/pertussis.Rout.save 2012-05-08 21:19:46 UTC (rev 712)
@@ -1,5 +1,5 @@
-R version 2.15.0 (2012-03-30)
+R Under development (unstable) (2012-05-07 r59324) -- "Unsuffered Consequences"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-unknown-linux-gnu (64-bit)
@@ -78,12 +78,12 @@
$SEIRR.big
time reports S E I R1 R2 cases W err simpop
-1036 19.90385 449 636820 4839 8046 3202063 1148211 3956 0 7 4999979
-1037 19.92308 472 637284 4951 8179 3201137 1148414 4114 0 7 4999965
-1038 19.94231 438 637653 5019 8240 3200093 1148879 4143 0 7 4999884
-1039 19.96154 474 637980 5084 8458 3199122 1149316 4261 0 7 4999960
-1040 19.98077 499 638422 4929 8626 3198103 1149922 4307 0 7 5000002
-1041 20.00000 469 639527 4413 8258 3196671 1151115 3834 0 7 4999984
+1036 19.90385 481 641670 4792 7924 3195207 1153657 3925 0 7 5003250
+1037 19.92308 379 642044 5038 8097 3193839 1154198 4018 0 7 5003216
+1038 19.94231 541 642462 5084 8425 3192769 1154480 4217 0 7 5003220
+1039 19.96154 577 642681 5221 8605 3192041 1154729 4331 0 7 5003277
+1040 19.98077 437 643030 5160 8849 3191258 1155014 4418 0 7 5003311
+1041 20.00000 400 644214 4588 8562 3189940 1155983 3884 0 7 5003287
$full.small
time reports S E I R1 R2 cases W err simpop
@@ -96,61 +96,61 @@
$full.big
time reports S E I R1 R2 cases W err
-1036 19.90385 381 685681 5306 8066 3166871 1137704 3943 -5.397648 7
-1037 19.92308 526 685987 5712 8423 3165789 1137727 4434 -5.215067 7
-1038 19.94231 406 686713 5594 8728 3164496 1138137 4487 -5.376581 7
-1039 19.96154 377 687178 5673 8981 3163446 1138391 4463 -5.484270 7
-1040 19.98077 549 687709 5515 9310 3162464 1138650 4717 -5.563903 7
-1041 20.00000 419 688789 4914 9220 3161008 1139607 4358 -5.568812 7
+1036 19.90385 319 624607 4552 7566 3278019 1088429 3664 -4.654307 7
+1037 19.92308 372 625824 4363 7590 3275577 1089789 3677 -4.795999 7
+1038 19.94231 348 626800 4490 7621 3273350 1090834 3689 -4.774106 7
+1039 19.96154 377 628074 4334 7672 3271128 1091904 3713 -4.848567 7
+1040 19.98077 331 629454 4185 7381 3268762 1093266 3431 -5.014912 7
+1041 20.00000 367 631218 3705 7153 3265743 1095129 3306 -4.966009 7
simpop
-1036 5003628
-1037 5003638
-1038 5003668
-1039 5003669
-1040 5003648
-1041 5003538
+1036 5003173
+1037 5003143
+1038 5003095
+1039 5003112
+1040 5003048
+1041 5002948
>
> x <- simulate(pertussis.sim$full.big,seed=395885L,as.data.frame=TRUE)
> tail(x)
- time reports S E I R1 R2 cases W err
-1036 19.90385 529 634087 5541 9277 3260155 1090900 4646 0.9650237 7
-1037 19.92308 345 634343 5687 9453 3259271 1091140 4625 0.9681362 7
-1038 19.94231 459 634432 6021 9647 3258692 1091145 4844 1.0560729 7
-1039 19.96154 391 634660 6040 9905 3258019 1091364 4918 1.0452093 7
-1040 19.98077 565 635319 5595 10107 3257412 1091594 5033 0.8786933 7
-1041 20.00000 411 636665 4728 9753 3256002 1092869 4394 0.7840614 7
+ time reports S E I R1 R2 cases W err
+1036 19.90385 432 662434 5677 9458 3201351 1118149 4831 -0.4801610 7
+1037 19.92308 524 662819 5615 9625 3200616 1118455 4737 -0.6165661 7
+1038 19.94231 396 662918 5888 9754 3200171 1118414 4831 -0.5954462 7
+1039 19.96154 515 663272 5698 9925 3199550 1118678 4928 -0.7923733 7
+1040 19.98077 504 663479 5812 9991 3198989 1118914 4782 -0.8369185 7
+1041 20.00000 529 664560 5030 9867 3197787 1119969 4609 -0.8803061 7
simpop sim
-1036 4999960 1
-1037 4999894 1
-1038 4999937 1
-1039 4999988 1
-1040 5000027 1
-1041 5000017 1
+1036 4997069 1
+1037 4997130 1
+1038 4997145 1
+1039 4997123 1
+1040 4997185 1
+1041 4997213 1
>
> y <- trajectory(pertussis.sim$SEIRS.small,as.data.frame=TRUE)
> tail(y)
- S E I R1 R2 cases W err simpop time
-1036 81409.73 558.4599 942.3100 227353.0 189736.5 0 0 0 5e+05 19.90385
-1037 81420.36 573.0107 965.5155 227305.3 189735.8 0 0 0 5e+05 19.92308
-1038 81418.14 587.5604 989.6877 227269.6 189735.0 0 0 0 5e+05 19.94231
-1039 81402.73 602.3328 1014.5493 227246.2 189734.2 0 0 0 5e+05 19.96154
-1040 81415.22 580.7639 1035.4780 227235.2 189733.4 0 0 0 5e+05 19.98077
-1041 81532.40 510.2405 1002.6699 227222.2 189732.5 0 0 0 5e+05 20.00000
- traj
-1036 1
-1037 1
-1038 1
-1039 1
-1040 1
-1041 1
+ S E I R1 R2 cases W err simpop
+1036 81409.73 558.4599 942.3100 227353.0 189736.5 487.2963 0 0 5e+05
+1037 81420.36 573.0107 965.5155 227305.3 189735.8 500.4770 0 0 5e+05
+1038 81418.14 587.5604 989.6877 227269.6 189735.0 513.3168 0 0 5e+05
+1039 81402.73 602.3328 1014.5493 227246.2 189734.2 526.2802 0 0 5e+05
+1040 81415.22 580.7639 1035.4780 227235.2 189733.4 534.7187 0 0 5e+05
+1041 81532.40 510.2405 1002.6699 227222.2 189732.5 478.9785 0 0 5e+05
+ time traj
+1036 19.90385 1
+1037 19.92308 1
+1038 19.94231 1
+1039 19.96154 1
+1040 19.98077 1
+1041 20.00000 1
>
> system.time(pf <- pfilter(pertussis.sim$full.small,seed=3445886L,Np=1000))
user system elapsed
- 20.957 0.000 21.018
+ 22.373 0.004 22.451
> logLik(pf)
[1] -3829.33
>
> proc.time()
user system elapsed
- 21.593 0.060 21.732
+ 22.857 0.040 22.985
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