Last updated on 2015-12-29 00:46:46.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-gcc | 1.3-3 | 147.52 | 39.50 | 187.02 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.3-3 | 586.86 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.3-3 | 387.72 | ERROR | |||
| r-devel-osx-x86_64-clang | 1.3-3 | 680.09 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 1.3-3 | 361.00 | 130.00 | 491.00 | ERROR | |
| r-patched-linux-x86_64 | 1.3-3 | 145.18 | 40.48 | 185.67 | NOTE | |
| r-patched-solaris-sparc | 1.3-3 | 1783.50 | NOTE | |||
| r-patched-solaris-x86 | 1.3-3 | 374.30 | NOTE | |||
| r-release-linux-x86_64 | 1.3-3 | 145.46 | 39.90 | 185.37 | NOTE | |
| r-release-osx-x86_64-mavericks | 1.3-3 | NOTE | ||||
| r-release-windows-ix86+x86_64 | 1.3-3 | 459.00 | 166.00 | 625.00 | NOTE | |
| r-oldrel-windows-ix86+x86_64 | 1.3-3 | 469.00 | 139.00 | 608.00 | NOTE |
Version: 1.3-3
Check: installed package size
Result: NOTE
installed size is 24.6Mb
sub-directories of 1Mb or more:
libs 23.9Mb
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64
Version: 1.3-3
Check: top-level files
Result: NOTE
Non-standard file/directory found at top level:
‘HISTORY’
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 1.3-3
Check: dependencies in R code
Result: NOTE
There are ::: calls to the package's namespace in its code. A package
almost never needs to use ::: for its own objects:
‘MCMCresidualBreakAnalysis’
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-osx-x86_64-clang, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64
Version: 1.3-3
Check: R code for possible problems
Result: NOTE
dtomogplot: no visible binding for global variable ‘heat.colors’
dtomogplot: no visible global function definition for ‘par’
dtomogplot: no visible global function definition for ‘layout’
dtomogplot: no visible global function definition for ‘lcm’
dtomogplot: no visible global function definition for ‘plot.new’
dtomogplot: no visible global function definition for ‘plot.window’
dtomogplot: no visible global function definition for ‘rect’
dtomogplot: no visible global function definition for ‘axis’
dtomogplot: no visible global function definition for ‘box’
dtomogplot: no visible global function definition for ‘plot’
dtomogplot: no visible global function definition for ‘abline’
mptable: no visible global function definition for ‘is’
plot.qrssvs: no visible global function definition for ‘dotplot’
plot.qrssvs : <anonymous>: no visible global function definition for
‘panel.abline’
plot.qrssvs : <anonymous>: no visible global function definition for
‘panel.dotplot’
plotChangepoint: no visible global function definition for ‘par’
plotChangepoint: no visible global function definition for ‘plot’
plotChangepoint: no visible global function definition for ‘axis’
plotChangepoint: no visible global function definition for ‘axTicks’
plotChangepoint: no visible global function definition for ‘lines’
plotIntervention: no visible global function definition for ‘plot’
plotIntervention: no visible global function definition for ‘abline’
plotIntervention: no visible global function definition for ‘lines’
plotState: no visible global function definition for ‘plot’
plotState: no visible global function definition for ‘axis’
plotState: no visible global function definition for ‘axTicks’
plotState: no visible global function definition for ‘lines’
plotState: no visible global function definition for ‘points’
plotState: no visible global function definition for ‘legend’
tomogplot: no visible global function definition for ‘par’
tomogplot: no visible global function definition for ‘plot’
tomogplot: no visible global function definition for ‘rect’
tomogplot: no visible global function definition for ‘abline’
tomogplot: no visible global function definition for ‘box’
topmodels: no visible global function definition for ‘is’
write.Scythe: no visible global function definition for ‘write.table’
Undefined global functions or variables:
abline axTicks axis box dotplot heat.colors is layout lcm legend
lines panel.abline panel.dotplot par plot plot.new plot.window points
rect write.table
Consider adding
importFrom("grDevices", "heat.colors")
importFrom("graphics", "abline", "axTicks", "axis", "box", "layout",
"lcm", "legend", "lines", "par", "plot", "plot.new",
"plot.window", "points", "rect")
importFrom("methods", "is")
importFrom("utils", "write.table")
to your NAMESPACE (and ensure that your DESCRIPTION Imports field
contains 'methods').
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64
Version: 1.3-3
Check: Rd line widths
Result: NOTE
Rd file 'HMMpanelFE.Rd':
\examples lines wider than 100 characters:
y[j:(j+T-1)] <- ((1-weight)*true.mean + (1-weight)*rnorm(T, 0, true.sigma) + (1-weight)*true.alpha1[i]) +
Rd file 'MCMCbinaryChange.Rd':
\examples lines wider than 100 characters:
model0 <- MCMCbinaryChange(y, m=0, c0=2, d0=2, mcmc=1000, burnin=1000, verbose=500, marginal.likelihood = "Chib95")
model1 <- MCMCbinaryChange(y, m=1, c0=2, d0=2, mcmc=1000, burnin=1000, verbose=500, marginal.likelihood = "Chib95")
model2 <- MCMCbinaryChange(y, m=2, c0=2, d0=2, mcmc=1000, burnin=1000, verbose=500, marginal.likelihood = "Chib95")
model3 <- MCMCbinaryChange(y, m=3, c0=2, d0=2, mcmc=1000, burnin=1000, verbose=500, marginal.likelihood = "Chib95")
model4 <- MCMCbinaryChange(y, m=4, c0=2, d0=2, mcmc=1000, burnin=1000, verbose=500, marginal.likelihood = "Chib95")
model5 <- MCMCbinaryChange(y, m=5, c0=2, d0=2, mcmc=1000, burnin=1000, verbose=500, marginal.likelihood = "Chib95")
Rd file 'MCMCintervention.Rd':
\usage lines wider than 90 characters:
prediction.type=c("trend","ar"), change.type=c("fixed", "random", "all"),
\examples lines wider than 100 characters:
plotIntervention(ar1fixed, start=1871, main="Forward Analysis", alpha= 0.5, ylab="Nile River flow", xlab="Year")
plotIntervention(ar1fixed, forward=FALSE, start=1871, main="Backward Analysis", alpha= 0.5, ylab="Nile River flow", xlab="Year")
Rd file 'MCMCirtHier1d.Rd':
\examples lines wider than 100 characters:
scMiss[matrix(as.logical(rbinom(nrow(SupremeCourt)*ncol(SupremeCourt), 1, .1)), dim(SupremeCourt))] <- NA
Rd file 'MCMCirtKdHet.Rd':
\examples lines wider than 100 characters:
"deviations from the party line are attributable","to idiosyncrasy rather than moderation."),cex=0.5)
Rd file 'MCMCregress.Rd':
\examples lines wider than 100 characters:
posterior <- MCMCregress(Y~X, b0=0, B0 = 0.1, sigma.mu = 5, sigma.var = 25, data=line, verbose=1000)
Rd file 'MCMCregressChange.Rd':
\examples lines wider than 100 characters:
model1 <- MCMCregressChange(formula, m=1, b0=b0, B0=B0, sigma.mu=sigma.mu, sigma.var=sigma.var, marginal.likelihood="Chib95")
model2 <- MCMCregressChange(formula, m=2, b0=b0, B0=B0, sigma.mu=sigma.mu, sigma.var=sigma.var, marginal.likelihood="Chib95")
model3 <- MCMCregressChange(formula, m=3, b0=b0, B0=B0, sigma.mu=sigma.mu, sigma.var=sigma.var, marginal.likelihood="Chib95")
model4 <- MCMCregressChange(formula, m=4, b0=b0, B0=B0, sigma.mu=sigma.mu, sigma.var=sigma.var, marginal.likelihood="Chib95")
model5 <- MCMCregressChange(formula, m=5, b0=b0, B0=B0, sigma.mu=sigma.mu, sigma.var=sigma.var, marginal.likelihood="Chib95")
Rd file 'plotState.Rd':
\usage lines wider than 90 characters:
plotState(mcmcout, main="Posterior Regime Probability", ylab=expression(paste("Pr(", S[t], "= k |", Y[t], ")")),
Rd file 'testpanelSubjectBreak.Rd':
\examples lines wider than 100 characters:
y[j:(j+T-1)] <- ((1-weight)*true.mean + (1-weight)*rnorm(T, 0, true.sigma) + (1-weight)*true.alpha1[i]) +
These lines will be truncated in the PDF manual.
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 1.3-3
Check: compilation flags in Makevars
Result: NOTE
Package has both ‘src/Makevars.in’ and ‘src/Makevars’.
Installation with --no-configure' is unlikely to work. If you intended
‘src/Makevars’ to be used on Windows, rename it to ‘src/Makevars.win’
otherwise remove it. If ‘configure’ created ‘src/Makevars’, you need a
‘cleanup’ script.
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-osx-x86_64-clang, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64
Version: 1.3-3
Check: examples
Result: ERROR
Running examples in ‘MCMCpack-Ex.R’ failed
The error most likely occurred in:
> ### Name: MCMCoprobitChange
> ### Title: Markov Chain Monte Carlo for Ordered Probit Changepoint
> ### Regression Model
> ### Aliases: MCMCoprobitChange
> ### Keywords: models
>
> ### ** Examples
>
> set.seed(1909)
> N <- 200
> x1 <- rnorm(N, 1, .5);
>
> ## set a true break at 100
> z1 <- 1 + x1[1:100] + rnorm(100);
> z2 <- 1 -0.2*x1[101:200] + rnorm(100);
> z <- c(z1, z2);
> y <- z
>
> ## generate y
> y[z < 1] <- 1;
> y[z >= 1 & z < 2] <- 2;
> y[z >= 2] <- 3;
>
> ## inputs
> formula <- y ~ x1
>
> ## fit multiple models with a varying number of breaks
> out1 <- MCMCoprobitChange(formula, m=1,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.30200
Acceptance rate for state 2 is 0.33400
The number of observations in state 1 is 00103
The number of observations in state 2 is 00097
beta 0 = 0.25560 0.53118
beta 1 = -0.09097 0.13030
gamma 0 = 0.79054
gamma 1 = 1.14920
logmarglike = -220.04555
loglike = -192.47056
log_prior = -4.31181
log_beta = 4.28397
log_P = 3.68247
log_gamma = 15.29673
> out2 <- MCMCoprobitChange(formula, m=2,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.53400
Acceptance rate for state 2 is 0.86800
Acceptance rate for state 3 is 0.22400
The number of observations in state 1 is 00107
The number of observations in state 2 is 00001
The number of observations in state 3 is 00092
beta 0 = 0.13360 0.70828
beta 1 = 0.22094 -0.47864
beta 2 = 0.40736 -0.28520
gamma 0 = 0.66271
gamma 1 = 5.38704
gamma 2 = 1.34721
logmarglike = -nan
loglike = -197.66532
log_prior = -7.77053
log_beta = 2.66115
log_P = 4.99484
log_gamma = -nan
> out3 <- MCMCoprobitChange(formula, m=3,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.24000
Acceptance rate for state 2 is 0.87600
Acceptance rate for state 3 is 0.64700
Acceptance rate for state 4 is 0.48900
The number of observations in state 1 is 00102
The number of observations in state 2 is 00003
The number of observations in state 3 is 00008
The number of observations in state 4 is 00087
beta 0 = -0.08525 0.82141
beta 1 = 0.15273 -0.06258
beta 2 = -0.24026 -0.10814
beta 3 = -0.49359 0.31134
gamma 0 = 0.95969
gamma 1 = 1.49675
gamma 2 = 23.05777
gamma 3 = 0.88755
logmarglike = -nan
loglike = -195.16892
log_prior = -10.05155
log_beta = 4.60715
log_P = 5.73137
log_gamma = -nan
>
> ## find the most reasonable one
> BayesFactor(out1, out2, out3)
Error in array(NA, M, dimnames = model.names) : 'dimnames' must be a list
Calls: BayesFactor -> array
Execution halted
Flavors: r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 1.3-3
Check: R code for possible problems
Result: NOTE
plot.qrssvs: no visible global function definition for ‘dotplot’
plot.qrssvs : <anonymous>: no visible global function definition for
‘panel.abline’
plot.qrssvs : <anonymous>: no visible global function definition for
‘panel.dotplot’
Undefined global functions or variables:
dotplot panel.abline panel.dotplot
Flavor: r-devel-osx-x86_64-clang
Version: 1.3-3
Check: examples
Result: ERROR
Running examples in ‘MCMCpack-Ex.R’ failed
The error most likely occurred in:
> ### Name: MCMCoprobitChange
> ### Title: Markov Chain Monte Carlo for Ordered Probit Changepoint
> ### Regression Model
> ### Aliases: MCMCoprobitChange
> ### Keywords: models
>
> ### ** Examples
>
> set.seed(1909)
> N <- 200
> x1 <- rnorm(N, 1, .5);
>
> ## set a true break at 100
> z1 <- 1 + x1[1:100] + rnorm(100);
> z2 <- 1 -0.2*x1[101:200] + rnorm(100);
> z <- c(z1, z2);
> y <- z
>
> ## generate y
> y[z < 1] <- 1;
> y[z >= 1 & z < 2] <- 2;
> y[z >= 2] <- 3;
>
> ## inputs
> formula <- y ~ x1
>
> ## fit multiple models with a varying number of breaks
> out1 <- MCMCoprobitChange(formula, m=1,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.30200
Acceptance rate for state 2 is 0.33400
The number of observations in state 1 is 00103
The number of observations in state 2 is 00097
beta 0 = 0.25560 0.53118
beta 1 = -0.09097 0.13030
gamma 0 = 0.79054
gamma 1 = 1.14920
logmarglike = -220.04555
loglike = -192.47056
log_prior = -4.31181
log_beta = 4.28397
log_P = 3.68247
log_gamma = 15.29673
> out2 <- MCMCoprobitChange(formula, m=2,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.53400
Acceptance rate for state 2 is 0.86800
Acceptance rate for state 3 is 0.22400
The number of observations in state 1 is 00107
The number of observations in state 2 is 00001
The number of observations in state 3 is 00092
beta 0 = 0.13360 0.70828
beta 1 = 0.22094 -0.47864
beta 2 = 0.40736 -0.28520
gamma 0 = 0.66271
gamma 1 = 5.38704
gamma 2 = 1.34721
logmarglike = nan
loglike = -197.66532
log_prior = -7.77053
log_beta = 2.66115
log_P = 4.99484
log_gamma = nan
> out3 <- MCMCoprobitChange(formula, m=3,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.24000
Acceptance rate for state 2 is 0.87600
Acceptance rate for state 3 is 0.64700
Acceptance rate for state 4 is 0.48900
The number of observations in state 1 is 00102
The number of observations in state 2 is 00003
The number of observations in state 3 is 00008
The number of observations in state 4 is 00087
beta 0 = -0.08525 0.82141
beta 1 = 0.15273 -0.06258
beta 2 = -0.24026 -0.10814
beta 3 = -0.49359 0.31134
gamma 0 = 0.95969
gamma 1 = 1.49675
gamma 2 = 23.05777
gamma 3 = 0.88755
logmarglike = nan
loglike = -195.16892
log_prior = -10.05155
log_beta = 4.60715
log_P = 5.73137
log_gamma = nan
>
> ## find the most reasonable one
> BayesFactor(out1, out2, out3)
Error in array(NA, M, dimnames = model.names) : 'dimnames' must be a list
Calls: BayesFactor -> array
Execution halted
Flavor: r-devel-osx-x86_64-clang
Version: 1.3-3
Check: running examples for arch ‘i386’
Result: ERROR
Running examples in 'MCMCpack-Ex.R' failed
The error most likely occurred in:
> ### Name: MCMCoprobitChange
> ### Title: Markov Chain Monte Carlo for Ordered Probit Changepoint
> ### Regression Model
> ### Aliases: MCMCoprobitChange
> ### Keywords: models
>
> ### ** Examples
>
> set.seed(1909)
> N <- 200
> x1 <- rnorm(N, 1, .5);
>
> ## set a true break at 100
> z1 <- 1 + x1[1:100] + rnorm(100);
> z2 <- 1 -0.2*x1[101:200] + rnorm(100);
> z <- c(z1, z2);
> y <- z
>
> ## generate y
> y[z < 1] <- 1;
> y[z >= 1 & z < 2] <- 2;
> y[z >= 2] <- 3;
>
> ## inputs
> formula <- y ~ x1
>
> ## fit multiple models with a varying number of breaks
> out1 <- MCMCoprobitChange(formula, m=1,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.30200
Acceptance rate for state 2 is 0.33400
The number of observations in state 1 is 00103
The number of observations in state 2 is 00097
beta 0 = 0.25560 0.53118
beta 1 = -0.09097 0.13030
gamma 0 = 0.79054
gamma 1 = 1.14920
logmarglike = -220.04555
loglike = -192.47056
log_prior = -4.31181
log_beta = 4.28397
log_P = 3.68247
log_gamma = 15.29673
> out2 <- MCMCoprobitChange(formula, m=2,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.53400
Acceptance rate for state 2 is 0.86800
Acceptance rate for state 3 is 0.22400
The number of observations in state 1 is 00107
The number of observations in state 2 is 00001
The number of observations in state 3 is 00092
beta 0 = 0.13360 0.70828
beta 1 = 0.22094 -0.47864
beta 2 = 0.40736 -0.28520
gamma 0 = 0.66271
gamma 1 = 5.38704
gamma 2 = 1.34721
logmarglike = nan
loglike = -197.66532
log_prior = -7.77053
log_beta = 2.66114
log_P = 4.99484
log_gamma = nan
> out3 <- MCMCoprobitChange(formula, m=3,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.24000
Acceptance rate for state 2 is 0.87600
Acceptance rate for state 3 is 0.64700
Acceptance rate for state 4 is 0.48900
The number of observations in state 1 is 00102
The number of observations in state 2 is 00003
The number of observations in state 3 is 00008
The number of observations in state 4 is 00087
beta 0 = -0.08525 0.82141
beta 1 = 0.15273 -0.06258
beta 2 = -0.24026 -0.10814
beta 3 = -0.49359 0.31134
gamma 0 = 0.95969
gamma 1 = 1.49675
gamma 2 = 23.05777
gamma 3 = 0.88755
logmarglike = nan
loglike = -195.16891
log_prior = -10.05154
log_beta = 4.60715
log_P = 5.73137
log_gamma = nan
>
> ## find the most reasonable one
> BayesFactor(out1, out2, out3)
Error in array(NA, M, dimnames = model.names) : 'dimnames' must be a list
Calls: BayesFactor -> array
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 1.3-3
Check: running examples for arch ‘x64’
Result: ERROR
Running examples in 'MCMCpack-Ex.R' failed
The error most likely occurred in:
> ### Name: MCMCoprobitChange
> ### Title: Markov Chain Monte Carlo for Ordered Probit Changepoint
> ### Regression Model
> ### Aliases: MCMCoprobitChange
> ### Keywords: models
>
> ### ** Examples
>
> set.seed(1909)
> N <- 200
> x1 <- rnorm(N, 1, .5);
>
> ## set a true break at 100
> z1 <- 1 + x1[1:100] + rnorm(100);
> z2 <- 1 -0.2*x1[101:200] + rnorm(100);
> z <- c(z1, z2);
> y <- z
>
> ## generate y
> y[z < 1] <- 1;
> y[z >= 1 & z < 2] <- 2;
> y[z >= 2] <- 3;
>
> ## inputs
> formula <- y ~ x1
>
> ## fit multiple models with a varying number of breaks
> out1 <- MCMCoprobitChange(formula, m=1,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.30200
Acceptance rate for state 2 is 0.33400
The number of observations in state 1 is 00103
The number of observations in state 2 is 00097
beta 0 = 0.25560 0.53118
beta 1 = -0.09097 0.13030
gamma 0 = 0.79054
gamma 1 = 1.14920
logmarglike = -220.04555
loglike = -192.47056
log_prior = -4.31181
log_beta = 4.28397
log_P = 3.68247
log_gamma = 15.29673
> out2 <- MCMCoprobitChange(formula, m=2,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.53400
Acceptance rate for state 2 is 0.86800
Acceptance rate for state 3 is 0.22400
The number of observations in state 1 is 00107
The number of observations in state 2 is 00001
The number of observations in state 3 is 00092
beta 0 = 0.13360 0.70828
beta 1 = 0.22094 -0.47864
beta 2 = 0.40736 -0.28520
gamma 0 = 0.66271
gamma 1 = 5.38704
gamma 2 = 1.34721
logmarglike = nan
loglike = -197.66532
log_prior = -7.77053
log_beta = 2.66115
log_P = 4.99484
log_gamma = nan
> out3 <- MCMCoprobitChange(formula, m=3,
+ mcmc=1000, burnin=1000, thin=1, tune=c(.5, .5, .5, .5), verbose=1000,
+ b0=0, B0=10, marginal.likelihood = "Chib95")
MCMCoprobitChange iteration 1001 of 2000
Acceptance rate for state 1 is 0.24000
Acceptance rate for state 2 is 0.87600
Acceptance rate for state 3 is 0.64700
Acceptance rate for state 4 is 0.48900
The number of observations in state 1 is 00102
The number of observations in state 2 is 00003
The number of observations in state 3 is 00008
The number of observations in state 4 is 00087
beta 0 = -0.08525 0.82141
beta 1 = 0.15273 -0.06258
beta 2 = -0.24026 -0.10814
beta 3 = -0.49359 0.31134
gamma 0 = 0.95969
gamma 1 = 1.49675
gamma 2 = 23.05777
gamma 3 = 0.88755
logmarglike = nan
loglike = -195.16892
log_prior = -10.05155
log_beta = 4.60715
log_P = 5.73137
log_gamma = nan
>
> ## find the most reasonable one
> BayesFactor(out1, out2, out3)
Error in array(NA, M, dimnames = model.names) : 'dimnames' must be a list
Calls: BayesFactor -> array
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 1.3-3
Check: R code for possible problems
Result: NOTE
plot.qrssvs: no visible global function definition for ‘dotplot’
plot.qrssvs : <anonymous>: no visible global function definition for
‘panel.abline’
plot.qrssvs : <anonymous>: no visible global function definition for
‘panel.dotplot’
Flavors: r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64