Secondary axis in R
plot(x) par(new = T) plot(y, axes = F, xlab = '', ylab = '') axis(4)
Secondary axis in R
plot(x) par(new = T) plot(y, axes = F, xlab = '', ylab = '') axis(4)
Compute or plot an empirical cumulative distribution function
ecdf()
Maximum-likelihood fitting of univariate distributions
fitdistr()
rug() presents the the data on the x-axis
Difference between density() and bkde()
They are also different in the default bandwidth.
Venables, W. N. and B. D. Ripley, (2002), Modern Applied Statitics with S (4th ed.), pp126-128
Difference between density() and bkde(); two kernel density estimation functions in R
On Mon, 18 Jan 2010, Mario Valle wrote:
> Any advice when to use denstity() and when the KernSmooth package bkde() to
> smooth a histogram?
>
> No specific problem to use either one, but I’m curious why there are two so
> similar implementations.
They are fundamentally different. density() uses FFT: bkde() does
not and is more flexible as a result Both use binning.
There are only a limited number of ways to implement something as
simple as KDE, and most of them have appeared in R/S-PLUS. Remember
that KernSmooth was written for S-PLUS and predates R (at least in
anything like its current form).
> Thanks!
> mario
>
> —
> Ing. Mario Valle
> Data Analysis and Visualization Group | http://www.cscs.ch/~mvalle
> Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60
> v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax: +41 (91) 610.82.82
>
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> and provide commented, minimal, self-contained, reproducible code.
>
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—
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