dbstats-package {dbstats}R Documentation

Distance-based statistics (dbstats)


This package contains functions for distance-based prediction methods.

These are methods for prediction where predictor information is coded as a matrix of distances between individuals.

In the currently implemented methods the response is a univariate variable as in the ordinary linear model or in the generalized linear model.

Distances can either be directly input as an distances matrix, a squared distances matrix, an inner-products matrix (see GtoD2) or computed from observed explanatory variables.

Notation convention: in distance-based methods we must distinguish observed explanatory variables which we denote by Z or z, from Euclidean coordinates which we denote by X or x. For explanation on the meaning of both terms see the bibliography references below.

Observed explanatory variables z are possibly a mixture of continuous and qualitative explanatory variables or more general quantities.

dbstats does not provide specific functions for computing distances, depending instead on other functions and packages, such as:

Functions of dbstats package:

Linear and local linear models with a continuous response:

Generalized linear and local generalized linear models with a numeric response:


Package: dbstats
Type: Package
Version: 2.0.2
Date: 2024-01-26
License: GPL-2
LazyLoad: yes


Boj, Eva <evaboj@ub.edu>, Caballe, Adria <adria.caballe@upc.edu>, Delicado, Pedro <pedro.delicado@upc.edu> and Fortiana, Josep <fortiana@ub.edu>


Boj E, Caballe, A., Delicado P, Esteve, A., Fortiana J (2016). Global and local distance-based generalized linear models. TEST 25, 170-195.

Boj E, Delicado P, Fortiana J (2010). Distance-based local linear regression for functional predictors. Computational Statistics and Data Analysis 54, 429-437.

Boj E, Grane A, Fortiana J, Claramunt MM (2007). Implementing PLS for distance-based regression: computational issues. Computational Statistics 22, 237-248.

Boj E, Grane A, Fortiana J, Claramunt MM (2007). Selection of predictors in distance-based regression. Communications in Statistics B - Simulation and Computation 36, 87-98.

Cuadras CM, Arenas C, Fortiana J (1996). Some computational aspects of a distance-based model for prediction. Communications in Statistics B - Simulation and Computation 25, 593-609.

Cuadras C, Arenas C (1990). A distance-based regression model for prediction with mixed data. Communications in Statistics A - Theory and Methods 19, 2261-2279.

Cuadras CM (1989). Distance analysis in discrimination and classification using both continuous and categorical variables. In: Y. Dodge (ed.), Statistical Data Analysis and Inference. Amsterdam, The Netherlands: North-Holland Publishing Co., pp. 459-473.

[Package dbstats version 2.0.2 Index]