isMonotoneL

Given a vector of n function values and an index ix, determines whether the function
values having indices less than or equal to ix are non-decreasing or non-increasing.
Returns TRUE if they are, FALSE otherwise.

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

isMonotoneL function

<dl><dt>f</dt>
<dd>A vector of function values for increasing abscissa values.</dd>
<dt>ix</dt>
<dd>An index giving the cutoff for checking monotonicity.</dd></dl>

Arguments

Check for monotonicity of function values in the left tail. — isMonotoneL

<dl>

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


<dt>ix</dt>
<dd>An index giving the cutoff for checking monotonicity.</dd>

</dl>

isMonotoneL: Check for monotonicity of function values in the left tail.

Description

Usage

Value

Arguments

Details