Out-of-sample forecast tests robust to the choice of window size

This paper proposes new methodologies for evaluating out-of-sample forecastingperformance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide rangeof window sizes. We show that the tests proposed in the literature may lack the powerto detect predictive ability and might be subject to data snooping across differentwindow sizes if used repeatedly. An empirical application shows the usefulness of themethodologies for evaluating exchange rate models' forecasting ability.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

Differences of Functional Connectivity Brain Network in Emotional Judgment

Using combined emotional stimuli, combining photos of faces and recording of voices, we investigated the neural dynamics of emotional judgment using scalp EEG recordings. Stimuli could be either combioned in a congruent, or a non-congruent way.. As many evidences show the major role of alpha in emotional processing, the alpha band was subjected to be analyzed. Analysis was performed by computing the synchronization of the EEGs and the conditions congruent vs. non-congruent were compared using statistical tools. The obtained results demonstrate that scalp EEG ccould be used as a tool to investigate the neural dynamics of emotional valence and discriminate various emotions (angry, happy and neutral stimuli).

A new heuristic method for solving spatially constrained forest planning problems based on mitigation of infeasibilities radiating outward from a forced choice

[Abstract]

Forest owners' acceptance of incentive based policy instruments in forest biodiversity conservation : a choice experiment based approach

Abstract

Reply to the letter to the editor "Freedom of choice".

Réponse au commentaire de: Gnädinger M. Freedom of choice. Swiss Med Wkly. 2012 Mar 22;142:0. doi:10.4414/smw.2012.13527. PMID: 22441992.

A Comparative Study: Service Animals and Emotional Support Animals under the Fair Housing Act and the Americans with Disabilities Act & An Overview of Assistance Animal Laws of Select States, April 18, 2010

The Americans with Disabilities Act (ADA) and the Fair Housing Act (FHA) prohibit discrimination on the basis of disability and govern the use of service or emotional support animals in places where pets may not be permitted. However, courts have been struggling with how to define and treat animals that qualify for protection under each law. This has created confusion as to what rights and duties are owed disabled persons and the animals that live with or accompany them. This essay attempts to clarify these two federal laws with regard to service or emotional support animals and the differing parties‘ rights and interests. It also includes an overview of select state laws that govern assistance animals of all types and our recommendations for enhancing the Iowa Civil Rights Act.

Construcción del Cuestionario de Desarrollo Emocional de Adultos (QDE-A).

El propósito de este trabajo es presentar la construcción y aplicación del Questionari de Desarrollo Emocional para Adultos (QDE-A). Se trata de la versión catalana del Cuestionario de Desarrollo Emocional para Adultos (CDE-A). Los instrumentos disponibles para la medición de la competencia emocional son escasos y todos ellos sujetos a criticas centradas fundamentalmente en la falta de un marco teórico claro y de fundamentos empíricos firmes (Pérez, Petrides y Furnham, 2005). El QDE-A, se enmarca en la línea de investigación sobre educación emocional del GROP (Grupo de Investigación en Orientación Psicopedagógica). Se trata de un cuestionario de autoinforme basado en el marco teórico de la educación emocional desarrollado por el GROP (Bisquerra, 2000 y 2007) según el cual la competencia emocional se compone de cinco dimensiones: conciencia emocional, regulación emocional, autonomía emocional competencias sociales y competencias para la vida y el bienestar. El QDE-A ofrece una puntuación global y otra para cada una de estas dimensiones. En este artículo se expone el proceso de elaboración para llegar a la versión definitiva que en su forma extensa consiste en una escala que dispone de 48 ítems. Los datos se basan en una muestra de 1537 adultos. La fiabilidad medida por el alfa de Cronbach es de 0,92, para la escala completa y superior a 0.70 para cada una de las dimensiones. La correlación entre cada una de las dimensiones y la puntuación total es significativa en todos los casos con un nivel de p<0.01. El QDE-A responde a la necesidad de disponer de un instrumento riguroso, adaptado a la población catalana, que permite evaluar el nivel de competencia emocional en adultos y fundamentar las intervenciones en educación emocional.

Emotional intelligence and social interest : are they related constructs?

In the last 15 years, a new psychological construct has emerged in the field of psychology: Emotional Intelligence. Some models of Emotional Intelligence bear ressemblence with aspects of one of the core constructs of Adlerian Psychology: Social Interest. The authors investigated, if both constructs are also empirically related and which is their capacity to predict psychiatric symptoms and antisocial behavior. Results indicate that Social Interest and Emotional Intelligence are empirically different constructs; Social Interest was negatively correlated to aspects of antisocial attitudes (but not to antisocial behavior). Social Interest also failed to predict symptoms of psychological distress. Emotional Intelligence, in change, was a better predictor for mental problems than Social Interest. The results are discussed in view of the validity of Social Interest measurement.