isBoundedL

Given a vector of n function values and an index ix, check whether values 1:ix are zero.
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

isBoundedL 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 for zero.</dd></dl>

Arguments

Check for zeros at the left side of a vector of function values. — isBoundedL

<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 for zero.</dd>

</dl>

isBoundedL: Check for zeros at the left side of a vector of function values.

Description

Usage

Value

Arguments

Details