[Pomp-commits] r125 - in pkg: . R data inst/examples man tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed May 13 14:08:32 CEST 2009
Author: kingaa
Date: 2009-05-13 14:08:32 +0200 (Wed, 13 May 2009)
New Revision: 125
Modified:
pkg/DESCRIPTION
pkg/R/simulate-pomp.R
pkg/data/euler.sir.rda
pkg/data/ou2.rda
pkg/data/rw2.rda
pkg/inst/examples/logistic.R
pkg/man/simulate-pomp.Rd
pkg/tests/logistic.R
pkg/tests/logistic.Rout.save
pkg/tests/ou2-nlf.R
pkg/tests/ou2-nlf.Rout.save
pkg/tests/ou2-simulate.R
pkg/tests/ou2-simulate.Rout.save
Log:
now when 'simulate' is called with nsim=1 (the default), a single 'pomp' object is returned rather than (per the old behavior) a list containing one 'pomp' object.
Modified: pkg/DESCRIPTION
===================================================================
--- pkg/DESCRIPTION 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/DESCRIPTION 2009-05-13 12:08:32 UTC (rev 125)
@@ -1,8 +1,8 @@
Package: pomp
Type: Package
Title: Statistical inference for partially observed Markov processes
-Version: 0.23-7
-Date: 2009-05-12
+Version: 0.24-1
+Date: 2009-05-13
Author: Aaron A. King, Edward L. Ionides, Carles Martinez Breto, Steve Ellner, Bruce Kendall
Maintainer: Aaron A. King <kingaa at umich.edu>
Description: Inference methods for partially-observed Markov processes
Modified: pkg/R/simulate-pomp.R
===================================================================
--- pkg/R/simulate-pomp.R 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/R/simulate-pomp.R 2009-05-13 12:08:32 UTC (rev 125)
@@ -57,6 +57,9 @@
po
}
)
+ if (nreps==1) {
+ retval <- retval[[1]]
+ }
} else {
if (!obs && states) { # return states only
retval <- x
Modified: pkg/data/euler.sir.rda
===================================================================
(Binary files differ)
Modified: pkg/data/ou2.rda
===================================================================
(Binary files differ)
Modified: pkg/data/rw2.rda
===================================================================
(Binary files differ)
Modified: pkg/inst/examples/logistic.R
===================================================================
--- pkg/inst/examples/logistic.R 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/inst/examples/logistic.R 2009-05-13 12:08:32 UTC (rev 125)
@@ -40,7 +40,7 @@
params <- c(n.0=10000,K=10000,r=0.9,sigma=0.4,tau=0.1)
set.seed(73658676)
-po <- simulate(po,params=params)[[1]]
+po <- simulate(po,params=params)
params <- cbind(c(n.0=100,K=10000,r=0.2,sigma=0.4,tau=0.1),c(n.0=1000,K=11000,r=0.1,sigma=0.4,tau=0.1))
x <- trajectory(po,params=params)
Modified: pkg/man/simulate-pomp.Rd
===================================================================
--- pkg/man/simulate-pomp.Rd 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/man/simulate-pomp.Rd 2009-05-13 12:08:32 UTC (rev 125)
@@ -35,6 +35,8 @@
Each has a simulated data set, together with the parameters used (in slot \code{params}) and the state trajectories also (in slot \code{states}).
If \code{times} is specified, then the \code{t0} slot of the created `pomp' objects will be filled with \code{times[1]} and the simulated observations will be at times \code{times[-1]}.
+ If \code{nsim=1}, then a single \code{pomp} object is returned (and not a singleton list).
+
If \code{states=TRUE} and \code{obs=FALSE}, simulated state trajectories are returned as a rank-3 array with dimensions \code{nvar} x \code{(ncol(params)*nsim)} x \code{ntimes}.
Here, \code{nvar} is the number of state variables and \code{ntimes} the length of the argument \code{times}.
The measurement process is not simulated in this case.
Modified: pkg/tests/logistic.R
===================================================================
--- pkg/tests/logistic.R 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/tests/logistic.R 2009-05-13 12:08:32 UTC (rev 125)
@@ -39,7 +39,7 @@
params <- c(n.0=10000,K=10000,r=0.9,sigma=0.4,tau=0.1)
set.seed(73658676)
-po <- simulate(po,params=params)[[1]]
+po <- simulate(po,params=params)
t <- seq(0,by=0.005,length=50)
x <- simulate(po,times=t,states=T,obs=T)
Modified: pkg/tests/logistic.Rout.save
===================================================================
--- pkg/tests/logistic.Rout.save 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/tests/logistic.Rout.save 2009-05-13 12:08:32 UTC (rev 125)
@@ -1,6 +1,6 @@
-R version 2.8.1 (2008-12-22)
-Copyright (C) 2008 The R Foundation for Statistical Computing
+R version 2.10.0 Under development (unstable) (2009-05-07 r48492)
+Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -58,7 +58,7 @@
>
> params <- c(n.0=10000,K=10000,r=0.9,sigma=0.4,tau=0.1)
> set.seed(73658676)
-> po <- simulate(po,params=params)[[1]]
+> po <- simulate(po,params=params)
>
> t <- seq(0,by=0.005,length=50)
> x <- simulate(po,times=t,states=T,obs=T)
Modified: pkg/tests/ou2-nlf.R
===================================================================
--- pkg/tests/ou2-nlf.R 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/tests/ou2-nlf.R 2009-05-13 12:08:32 UTC (rev 125)
@@ -6,7 +6,7 @@
po <- ou2
coef(po,c("x1.0","x2.0","alpha.1","alpha.4")) <- c(0,0,0.1,0.2)
-po <- simulate(po,times=(1:10000))[[1]]
+po <- simulate(po,times=(1:10000))
p.truth <- coef(po)
guess <- p.truth
## guess[c('x1.0','x2.0','alpha.1','alpha.4')] <- c(45,-60,0.8,0.9)
Modified: pkg/tests/ou2-nlf.Rout.save
===================================================================
--- pkg/tests/ou2-nlf.Rout.save 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/tests/ou2-nlf.Rout.save 2009-05-13 12:08:32 UTC (rev 125)
@@ -1,6 +1,6 @@
-R version 2.7.2 (2008-08-25)
-Copyright (C) 2008 The R Foundation for Statistical Computing
+R version 2.10.0 Under development (unstable) (2009-05-07 r48492)
+Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -16,7 +16,8 @@
Type 'q()' to quit R.
> library(pomp)
-Loading required package: odesolve
+Loading required package: deSolve
+Loading required package: subplex
>
> data(ou2)
>
@@ -24,7 +25,7 @@
>
> po <- ou2
> coef(po,c("x1.0","x2.0","alpha.1","alpha.4")) <- c(0,0,0.1,0.2)
-> po <- simulate(po,times=(1:10000))[[1]]
+> po <- simulate(po,times=(1:10000))
> p.truth <- coef(po)
> guess <- p.truth
> ## guess[c('x1.0','x2.0','alpha.1','alpha.4')] <- c(45,-60,0.8,0.9)
@@ -61,8 +62,8 @@
25 function evaluations used
h in NLF = 0.1
epsilon in NLF = 0.4420236 0.2750263
-Fitted param 1 -4.042142 -4.042142 up in ‘nlf’
-Fitted param 1 -4.031832 down in ‘NLF’
-Fitted param 2 -4.032517 -4.032517 up in ‘nlf’
-Fitted param 2 -4.03145 down in ‘NLF’
+Fitted param 1 -4.042142 -4.042142 up in 'nlf'
+Fitted param 1 -4.031832 down in 'NLF'
+Fitted param 2 -4.032517 -4.032517 up in 'nlf'
+Fitted param 2 -4.03145 down in 'NLF'
>
Modified: pkg/tests/ou2-simulate.R
===================================================================
--- pkg/tests/ou2-simulate.R 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/tests/ou2-simulate.R 2009-05-13 12:08:32 UTC (rev 125)
@@ -17,7 +17,7 @@
coef(ou2,c('x1.0','x2.0')) <- c(-50,50)
-ou2.sim <- simulate(ou2)[[1]]
+ou2.sim <- simulate(ou2)
x <- simulate(ou2,nsim=3,states=T)
y <- simulate(ou2,nsim=3,obs=T)
z <- simulate(ou2,nsim=3,obs=T,states=T)
Modified: pkg/tests/ou2-simulate.Rout.save
===================================================================
--- pkg/tests/ou2-simulate.Rout.save 2009-05-12 17:34:37 UTC (rev 124)
+++ pkg/tests/ou2-simulate.Rout.save 2009-05-13 12:08:32 UTC (rev 125)
@@ -1,6 +1,6 @@
-R version 2.6.1 (2007-11-26)
-Copyright (C) 2007 The R Foundation for Statistical Computing
+R version 2.10.0 Under development (unstable) (2009-05-07 r48492)
+Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -16,6 +16,8 @@
Type 'q()' to quit R.
> library(pomp)
+Loading required package: deSolve
+Loading required package: subplex
>
> data(ou2)
>
@@ -31,11 +33,11 @@
> ou2.sim <- simulate(ou2,params=p,nsim=100,seed=32043858)
> toc <- Sys.time()
> print(toc-tic)
-Time difference of 0.2832530 secs
+Time difference of 0.3552971 secs
>
> coef(ou2,c('x1.0','x2.0')) <- c(-50,50)
>
-> ou2.sim <- simulate(ou2)[[1]]
+> ou2.sim <- simulate(ou2)
> x <- simulate(ou2,nsim=3,states=T)
> y <- simulate(ou2,nsim=3,obs=T)
> z <- simulate(ou2,nsim=3,obs=T,states=T)
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