Compute robust (quantile based) statistics from probability distributions.
ph.median (xf, …)
ph.quantile (xf, p, …)iqr (xf, P=0.5, …)
A numeric vector, suitable function object, or an object that can be coerced to a numeric vector. Here, a suitable function object is a quantile function. Refer to the references and see also sections.
Numeric vectors, the probabilities. P is the area (probability) between the lower and upper limits.
Other arguments. Refer to the details section.
ph.median returns a single numeric value.
The other functions return a numeric vector.
If xf is a numeric vector, a qfuv.el object is created using xf as the main argument. Any arguments contained within …, are passed to the qfuv.el constructor.
If xf is not a quantile function, these functions try to coerce it to a numeric vector, and apply the above.
Refer to the vignette for an overview, references and better examples.
Succinct Constructors Discrete Kernel Smoothing, Continuous Kernel Smoothing, Empirical-Like Distributions
# NOT RUN {
prep.ph.data ()
cFht <- qfuv.cks (height)
cFht (0.5)
ph.median (cFht)
#iqr (cFht)
# }
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