post.predict.ggdmc: Simulate Post-predictive Sample
In TasCL/ggdmc: Dynamic Model of Choice with Parallel Computation, and C++ Capabilities
Description
Make a list of probability density, quantiles and resposnes based on a
posterior DMC sample. This function is to produce a data frame that can be
used by ggplot2 functions.
Usage
1
2
post.predict.ggdmc(samples, n.post = 100, probs = c(1:99)/100,
bw = "nrd0", report = 10, save.dat = FALSE)
Arguments
samples
a DMC sample/object
n.post
how many data point to simulate
probs
the quantile probability. Default c(1:99)/100
bw
bin width method. Default "nrd0", passing to density function
report
report progress
save.dat
whether to save simulation data to further modify data
frame for plotting
TasCL/ggdmc documentation built on May 9, 2019, 4:19 p.m.
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Description
Make a list of probability density, quantiles and resposnes based on a posterior DMC sample. This function is to produce a data frame that can be used by ggplot2 functions.
Usage
1 2 | post.predict.ggdmc(samples, n.post = 100, probs = c(1:99)/100,
bw = "nrd0", report = 10, save.dat = FALSE)
|
Arguments
samples |
a DMC sample/object |
n.post |
how many data point to simulate |
probs |
the quantile probability. Default c(1:99)/100 |
bw |
bin width method. Default "nrd0", passing to density function |
report |
report progress |
save.dat |
whether to save simulation data to further modify data frame for plotting |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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