Using the R-MAPE index as a resistant measure of forecast accuracy.

Background: The mean absolute percentage error (MAPE) is probably the most widely used goodness-of-fit measure. However, it does not meet the validity criterion due to the fact that the distribution of the absolute percentage errors is usually skewed to the right, with the presence of outlier values. In these cases, MAPE overstates the corresponding population parameter.

The two-way mixed model: a long and winding controversy.

Background: With the 2-way mixed model, one a fixed factor and the other random, the procedure followed to test statistical significance of the random factor has been the focus of a heated controversy in theoretical and applied statistics, and the debating continues even now. One of the main consequences of this controversy is that the position defended in the classical ANOVA texts on the hypothesis of the significance of the random effect is not the same as that defended in almost all of the professional statistical software programs.

Method: In this paper, we deal with a detailed analysis about the controversy of mixed model and the decision about one of two basic options, the non restrictive and the restrictive model.

Artificial neural networks applied to forecasting time series.

This study offers a description and comparison of the main models of Artificial Neural Networks (ANN) which have proved to be useful in time series forecasting, and also a standard procedure for the practical application of ANN in this type of task. The Multilayer Perceptron (MLP), Radial Base Function (RBF), Generalized Regression Neural Network (GRNN), and Recurrent Neural Network (RNN) models are analyzed. With this aim in mind, we use a time series made up of 244 time points.

Study of the factors associated with substance use in adolescence using Association Rules.

The aim of this study is to analyse the factors related to the use of addictive substances in adolescence using association rules, descriptive tools included in Data Mining. Thus, we have a database referring to the consumption of addictive substances in adolescence, and use the free distribution program in the R arules package (version 2.10.

[Generic skills in higher education. Comparative study of the views of employers and academics].

This paper analyzes and compares employers' and academics' views on the importance of generic skills in training graduates and the level acquired in higher education. We used a sample of 500 companies and public institutions in the Balearic Islands that have university graduates among their employees and a sample of 173 academics from the University of the Balearic Islands. We used survey methodology to collect the data and compared the descriptive results of these two groups.

The methodology of Data Mining. An application to alcohol consumption in teenagers.

This paper is aimed mainly at making researchers in the field of drug addictions aware of a methodology of data analysis aimed at knowledge discovery in databases (KDD). KDD is a process consisting of a series of phases, the most characteristic of which is called data mining (DM), whereby different modelling techniques are applied in order to detect patterns and relationships among the data. Common and differentiating factors between the most widely used DM techniques are analysed, mainly from a methodological viewpoint, and their use is exemplified using data related to alcohol consumption in teenagers and its possible relationship with personality variables (N=7030).

Activity levels and drug use in a sample of Spanish adolescents.

The importance of adolescents taking part in various activities as a protective factor in substance consumption has been demonstrated over time. The objective of this paper is to analyze a sample of 1378 adolescents and the explanatory capacity of participating in different activities in relation to present-day alcohol, cannabis and tobacco consumption. Count variables were used as response variables, thus the Poisson Regression Model was applied in the analysis, within the context of a Generalized Linear Model.