An investigation of imputation methods for discrete databases and multi-variate time series

When it comes to information sets in real life, often pieces of the whole set may not be available. This problem can find its origin in various reasons, describing therefore different patterns. In the literature, this problem is known as Missing Data. This issue can be fixed in various ways, from not taking into consideration incomplete observations, to guessing what those values originally were, or just ignoring the fact that some values are missing. The methods used to estimate missing data are called Imputation Methods. The work presented in this thesis has two main goals. The first one is to determine whether any kind of interactions exists between Missing Data, Imputation Methods and Supervised Classification algorithms, when they are applied together. For this first problem we consider a scenario in which the databases used are discrete, understanding discrete as that it is assumed that there is no relation between observations. These datasets underwent processes involving different combina- tions of the three components mentioned. The outcome showed that the missing data pattern strongly influences the outcome produced by a classifier. Also, in some of the cases, the complex imputation techniques investigated in the thesis were able to obtain better results than simple ones. The second goal of this work is to propose a new imputation strategy, but this time we constrain the specifications of the previous problem to a special kind of datasets, the multivariate Time Series. We designed new imputation techniques for this particular domain, and combined them with some of the contrasted strategies tested in the pre- vious chapter of this thesis. The time series also were subjected to processes involving missing data and imputation to finally propose an overall better imputation method. In the final chapter of this work, a real-world example is presented, describing a wa- ter quality prediction problem. The databases that characterized this problem had their own original latent values, which provides a real-world benchmark to test the algorithms developed in this thesis.

Lowndes and Locke on the value of money

This paper was presented at the 11th Annual Conference of the European Society for the History of Economic Thought (ESHET).

Adam Smith on labour and value: challenging the standard interpretation

This paper was presented at the Seminars of the Department of Foundations of Economic Analysis I, University of the Basque Country in September 2004.

Morals in business organizations: an approach based on strategic value and strength for business management

[EN] In the last decades, the topic of business ethics has attracted great interest at the academic and professional levels. Nowadays business ethics is being increasingly implemented as a necessary discipline in universities’ study plans on business management. Moreover, its importance is also evident according to the worldwide increase of organizations and/or institutions that have implemented ethics systems. However, some approaches thoroughly do not consider the importance and the need of an ethical behaviour and are still guiding the actions and the way of thinking of many academics and professionals led to consider that the only responsibility of business is limited just to profit maximization.

Using the system dynamics paradigm in teaching and learning technological university subjets

2nd International Conference on Education and New Learning Technologies

Discounting the value of natural resources in costbenefit analysis: a case study for policy making

4 p.

The Equivalency Principle for Discounting the Value of Natural Assets: An Application to an Investment Project in the Basque Coast

25 p.