bandwidth_CI

A function for the selection of optimal multivariate mixed bandwidths for the kernel
density estimation of continuous and discrete exogenous variables.

A collection of functions to calculate Composite Indicators methods, focusing, in particular, on the normalisation and weighting-aggregation steps, as described in OECD Handbook on constructing composite indicators: methodology and user guide, 2008, 'Vidoli' and 'Fusco' and 'Mazziotta' <doi:10.1007/s11205-014-0710-y>, 'Mazziotta' and 'Pareto' (2016) <doi:10.1007/s11205-015-0998-2>, 'Van Puyenbroeck and 'Rogge' <doi:10.1016/j.ejor.2016.07.038> and other authors.

Francesco Vidoli

Compind

Composite Indicators Functions

Elisa Fusco

bandwidth_CI function

<dl> <dt>x</dt>
<dd>A data frame containing simple indicators.</dd> <dt>indic_col</dt>
<dd>Simple indicators column number.</dd> <dt>ngood</dt>
<dd>The number of desirable outputs; it has to be greater than 0.</dd> <dt>nbad</dt>
<dd>The number of undesirable outputs; it has to be greater than 0.</dd> <dt>Q</dt>
<dd>A matrix containing continuous exogenous variables.</dd> <dt>Q_ord</dt>
<dd>A matrix containing discrete exogenous variables.</dd></dl>

Arguments

Author

Multivariate mixed bandwidth selection for exogenous variables — bandwidth_CI

<dl>

 <dt>x</dt>
<dd>A data frame containing simple indicators.</dd>

 <dt>indic_col</dt>
<dd>Simple indicators column number.</dd>

 <dt>ngood</dt>
<dd>The number of desirable outputs; it has to be greater than 0.</dd>

 <dt>nbad</dt>
<dd>The number of undesirable outputs; it has to be greater than 0.</dd>

 <dt>Q</dt>
<dd>A matrix containing continuous exogenous variables.</dd>

 <dt>Q_ord</dt>
<dd>A matrix containing discrete exogenous variables.</dd>

</dl>

bandwidth_CI: Multivariate mixed bandwidth selection for exogenous variables

Description

Usage

Value

Arguments

Author

Details

Examples