plotSamples {LaplacesDemon} | R Documentation |
Plot Samples
Description
This function provides basic plots that are extended to include samples.
Usage
plotSamples(X, Style="KDE", LB=0.025, UB=0.975, Title=NULL)
Arguments
X |
This required argument is a |
Style |
This argument accepts the following quoted strings:
"barplot", "dotchart", "hist", "KDE", or "Time-Series". It defaults
to |
LB |
This argument accepts the lower bound of a probability interval, which must be in the interval [0,0.5). |
UB |
This argument accepts the upper bound of a probability interval, which must be in the interval (0.5,1]. |
Title |
This argument defaults to |
Details
The plotSamples
function extends several basic plots from
points to samples. For example, it is common to use the hist
function to plot a histogram from a column vector. However, the user
may desire to plot a histogram of a column vector that was sampled
numerous times, rather than a simple column vector, in which a
(usually 95%) probability interval is also plotted to show the
uncertainty around the sampled median of each bin in the histogram.
The plotSamples
function extends the barplot
,
dotchart
, and hist
functions to include uncertainty due
to samples. The KDE
style of plot is added so that a
probability interval is shown around a sampled kernel density estimate
of a distribution, and the Time-Series
style of plot is added
so that a probability interval is shown around a sampled univariate
time-series.
For each style of plot, three quantiles are plotted: the lower bound (LB), median, and upper bound (UB).
One of many potential Bayesian applications is to examine the uncertainty in a predictive distribution.
Author(s)
Statisticat, LLC. software@bayesian-inference.com
Examples
#library(LaplacesDemon)
#N <- 100
#S <- 100
#X <- matrix(rnorm(N*S),N,S)
#rownames(X) <- 1:100
#plotSamples(X, Style="barplot", LB=0.025, UB=0.975)
#plotSamples(X[1:10,], Style="dotchart", LB=0.025, UB=0.975)
#plotSamples(X, Style="hist", LB=0.025, UB=0.975)
#plotSamples(X, Style="KDE", LB=0.025, UB=0.975)
#plotSamples(X, Style="Time-Series", LB=0.025, UB=0.975)