Journal ArticleDOI
A distance based regression model for prediction with mixed data
Reads0
Chats0
TLDR
In this article, a multiple regression method based on distance analysis and metric scaling is proposed and studied to predict a continuous response variable from several explanatory variables, which is compatible with the general linear model and is found to be useful when the predictor variables are both continuous and categorical.Abstract:
A multiple regression method based on distance analysis and metric scaling is proposed and studied. This method allow us to predict a continuous response variable from several explanatory variables, is compatible with the general linear model and is found to be useful when the predictor variables are both continuous and categorical. Real data examples are given to illustrate the results obtained.read more
Citations
More filters
Journal ArticleDOI
Three-dimensional quantitative structure-activity relationships from tuned molecular quantum similarity measures: prediction of the corticosteroid-binding globulin binding affinity for a steroid family.
TL;DR: The corticosteroid-binding globulin binding affinity of a 31 steroid family is studied by means of a multilinear regression using molecular descriptors derived from mixed steric-electrostatic quantum similarity matrixes as parameters, obtaining satisfactory predictions.
Posted Content
Local Distance-Based Generalized Linear Models Using the Dbstats Package for R
TL;DR: These models extend (weighted) distance-based linear models firstly with the generalized linear model concept, then by localizing, and are applicable to mixed (qualitative and quantitative) explanatory variables or when the regressor is of functional type.
Journal ArticleDOI
Analysis of distance for structured multivariate data and extensions to multivariate analysis of variance
TL;DR: In this paper, the authors examine the structure of distance matrices in the presence of a priori grouping of units and show how the total squared distance among the units of a multivariate data set can be partitioned according to the factors of an external classification.
References
More filters
Book
Principal Component Analysis
TL;DR: In this article, the authors present a graphical representation of data using Principal Component Analysis (PCA) for time series and other non-independent data, as well as a generalization and adaptation of principal component analysis.
Journal ArticleDOI
A General Coefficient of Similarity and Some of Its Properties
TL;DR: A general coefficient measuring the similarity between two sampling units is defined and the matrix of similarities between all pairs of sample units is shown to be positive semidefinite.
Journal ArticleDOI
Some distance properties of latent root and vector methods used in multivariate analysis
TL;DR: In this paper, the authors derived necessary and sufficient conditions for a solution to exist in real Euclidean space for a multivariate multivariate sample of size n as points P1, P2,..., PI in a Euclidian space and discussed the interpretation of the distance A(Pi, Pj) between the ith and jth members of the sample.
Book
Applied Linear Regression
TL;DR: In this paper, the authors present a method to estimate the least squares of a scatterplot matrix using a simple linear regression model, and compare it with the mean function of the scatterplot matrices.