Description Usage Arguments Details Value References See Also Examples
Bivariate kernel density estimates and bivariate empirical cumulative distribution functions.
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x, y |
Equal length numeric vectors, of x and y values. |
xbw, ybw |
Optional numeric values, giving the x and y bandwidths. |
xsmoothness, ysmoothness |
Numeric scalars, giving the relative smoothness. |
data |
A two-column data.frame object. |
... |
Ignored. |
Default xlab and ylab labels are taken for deparsed x and y names.
(Unless data is provided, in which case, column names are used).
Bandwidth parameters are optional, however, the default values are likely to be sub-optimal.
Kernel density estimates use KernSmooth::bkde2D.
Self-referencing S4-based function objects.
Refer to Function Objects.
Note that you can't evaluate the function representing kernel density estimates.
(However, the bvmat function can be used to compute density matrices).
Refer to the vignette for an overview, references, theoretical background and better examples.
Note that the probhat package provides more tools for kernel smoothing.
Uniform
For uniform distributions.
Binomial, Poisson and Categorical
For other probability distributions of discrete random variables.
Normal, Bimodal and Dirichlet
For other probability distributions of continuous random variables.
Main Plotting Functions
Density Matrices
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#kernel density estimates
########################################
data ("geyser", package="MASS")
attach (geyser)
#adapted from the KernSmooth package
fh <- kbvpdf (duration, waiting, 0.7, 7)
plot (fh,, TRUE)
plot (fh, TRUE, z.axis=TRUE, ref.arrows=FALSE)
detach (geyser)
########################################
#ECDF
########################################
attach (trees)
Fh <- ebvcdf (Height, Volume)
plot (Fh)
plot (Fh, FALSE)
Fh (median (Height), mean (Volume) )
detach (trees)
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