isUnimodal

Given a set of function values for increasing abscissa values, we call this unimodal if
there are zero or one values that are greater than all of their neighbors. Before
checking for modes, the values are scaled to fill [0, 1] and then rounded to four
decimal places. This eliminates unwanted detection of tiny differences as modes.

internal

Implements methods for obtaining kernel density estimates
subject to a variety of shape constraints (unimodality, bimodality,
symmetry, tail monotonicity, bounds, and constraints on the number of
inflection points). Enforcing constraints can eliminate unwanted waves or
kinks in the estimate, which improves its subjective appearance and can
also improve statistical performance. The main function scdensity() is
very similar to the density() function in 'stats', allowing
shape-restricted estimates to be obtained with little effort. The
methods implemented in this package are described in Wolters and Braun
(2017) <doi:10.1080/03610918.2017.1288247>, Wolters (2012)
<doi:10.18637/jss.v047.i06>, and Hall and Huang (2002)
<https://www3.stat.sinica.edu.tw/statistica/j12n4/j12n41/j12n41.htm>.
See the scdensity() help for for full citations.

Mark A Wolters

scdensity

Shape-Constrained Kernel Density Estimation

isUnimodal function

<dl><dt>f</dt>
<dd>A vector of function values for increasing abscissa values.</dd></dl>

Arguments

Check for unimodality of function values. — isUnimodal

<dl>

<dt>f</dt>
<dd>A vector of function values for increasing abscissa values.</dd>

</dl>

isUnimodal: Check for unimodality of function values.

Description

Usage

Value

Arguments

Details