State Space Methods in Ox/SsfPack

The use of state space models and their inference is illustrated using the package SsfPack for Ox. After a rather long introduction that explains the use of SsfPack and many of its functions, four case-studies illustrate the practical implementation of the software to real world problems through short sample programs. The first case consists in the analysis of the well-known (at least to time series analysis experts) Nile data with a local level model. The other case-studies deal with ARIMA and RegARIMA models applied to the (also well-known) Airline time series, structural time series models applied to the Italian industrial production index and stochastic volatility models applied to the FTSE100 index. In all applications inference on the model (hyper-) parameters is carried out by maximum likelihood, but in one case (stochastic volatility) also an MCMC-based approach is illustrated. Cubic splines are covered in a very short example as well.

Business cycle and sector cycles

A methodology based on the multivariate generalized Butterwoth filter for extracting the business cycles of the whole economy and of its productive sectors is developed. The method is then illustrated through an application to the Italian gross value added time series of the main economic sectors.Business cycle, Butterworth filter, Unobserved components, Kalman Filter

Time Series Modeling with Duration Dependent Markov-Switching Vector Autoregressions: MCMC Inference, Software and Applications

Duration dependent Markov-switching VAR (DDMS-VAR) models are time series models with data generating process consisting in a mixture of two VAR processes, which switches according to a two-state Markov chain with transition probabilities depending on how long the process has been in a state. In the present paper I propose a MCMC-based methodology to carry out inference on the model's parameters and introduce DDMSVAR for Ox, a software written by the author for the analysis of time series by means of DDMS-VAR models. An application of the methodology to the U.S. business cycle concludes the article.Markov-switching, Business cycle, Gibbs sampling, Duration dependence, Vector autoregression

Dynamic Conditional Correlation with Elliptical Distributions

The Dynamic Conditional Correlation model of Engle has made the estimation of multivariate GARCH models feasible for reasonably big vectors of securities’ returns. In the present paper we show how Engle’s twosteps estimate of the model can be easily extended to elliptical conditional distributions and apply different leptokurtic DCC models to some stocks listed at the Milan Stock Exchange. A free software written by the authors to carry out all the required computations is presented as well.Multivariate GARCH, Dynamic conditional correlation, Generalized method of moments

State Space Methods in Ox/SsfPack

The use of state space models and their inference is illustrated using the package SsfPack for Ox. After a rather long introduction that explains the use of SsfPack and many of its functions, four case-studies illustrate the practical implementation of the software to real world problems through short sample programs. The first case consists in the analysis of the well-known (at least to time series analysis experts) Nile data with a local level model. The other case-studies deal with ARIMA and RegARIMA models applied to the (also well-known) Airline time series, structural time series models applied to the Italian industrial production index and stochastic volatility models applied to the FTSE100 index. In all applications inference on the model (hyper-) parameters is carried out by maximum likelihood, but in one case (stochastic volatility) also an MCMC-based approach is illustrated. Cubic splines are covered in a very short example as well

Idmb: a tool for navigating the Inspire data model and generating an Inspire SQL database and WFS Configuration

The Inspire Data Model Browser (IDMB) is a free tool that performs the following functions: (i) it presents the Inspire UML Data Model as a tree-based structure, which is complementary to the UML diagrams; (ii) it generates a Postgis SQL Script for creating an INSPIRE compliant SQL database (Inspire Database) and a configuration file for the Deegree tool that enables the access to the Inspire Database through a Web Feature Service (WFS) producing GML according to the Inspire XML Schemas

A closer look at the timecourse of mind wandering: Pupillary responses and behaviour

Mind wandering (MW) refers to the shift of attention away from a primary task and/or external environment towards thoughts unrelated to the task. Recent evidence has shown that pupillometry can be used as an objective marker of the onset and maintenance of externally-driven MW episodes. In the present study we aimed to further investigate pupillary changes associated with the onset and duration of self-reported MW episodes. We used a modified version of the joint behavioural-pupillometry paradigm we recently introduced. Participants were asked to perform a monotonous vigilance task which was intermixed with task-irrelevant cue-phrases (visually presented verbal cues); they were instructed to interrupt the task whenever a thought came to mind (self-caught method) and to indicate the trigger of their thought, if any. We found systematic pupil dilation after the presentation of verbal cues reported to have triggered MW, compared with other verbal cues presented during a supposedly on-task period (i.e., the period immediately following the resuming of the task after a self-caught interruption and MW report). These results confirm that pupil diameter is sensitive to the changes associated with the onset of MW and its unfolding over time. Moreover, by computing the latency between the trigger presentation and the task interruption (self-catch), we could also estimate the duration of MW episodes triggered by verbal cues. However, a high variability was found, implying very large inter-event variability, which could not be explained by any of the MW properties we acquired (including: temporal focus, specificity, emotional valence). Our behavioural and pupillometry findings stress the need for objective measures about the temporal unfolding of MW (while most studies focus on arbitrary time-window preceding self-reports of MW)

Application of the GeoUML Tools for the Production and Validation of Inspire Datasets

The structure of INSPIRE datasets is oriented to the exchange of data, not to its storage and manipulation in a database. Therefore data transformation is required. This paper analyses the possibility of using in this context the tools developed by SpatialDBGroup at Politecnico di Milano in order to create and validate spatial databases. The considered scenario is the following one: - an organisation (data provider) is willing to provide WFS and GML conformant to INSPIRE specifications (services and data); - this organisation is hosting geodata related to one or more INSPIRE themes on a spatial relational database, called here Source Database - in order to facilitate the implementation of INSPIRE compliant GML data, the organisation implements a new "INSPIRE-structured" spatial database, called here INSPIRE Database - a Transformation Procedure is created which extracts the data from the Source Database and loads it into the INSPIRE Database - the INSPIRE Database is "validated" also using topological operators, in order to identify also topological constraints gaps. We assume that both the Source Database and the INSPIRE Database are SQL based and that their physical schemas have been generated by the GeoUML Catalogue tool from the corresponding conceptual schemas, called SCSOURCE and SCINSPIRE. In this scenario the availability of the conceptual schemas suggests different areas where the tools can provide a great benefit: 1. Creation of the GeoUML specification SCINSPIRE, automatic generation of the corresponding physical SQL structure and Validation of the INSPIRE Database with respect to the specification 2. (Semi)automatic generation of the Transformation Procedure using a set of correspondence rules between elements of SCSOURCE and SCINSPIRE 3. Automatic generation of the WFS configuration from the SCINSPIRE In this paper we describe the work which has already been done and the research directions which we are following in order to deal with these points

Statistical investigation on the relation between car accidents and warm katabatic winds

The possible relationship between warm katabatic winds and human health and behaviour is analyzed; notwithstanding popular belief which is very positive about it, the connection has not been previously analyzed with the proper methods. We use a statistical model to address this question and our data suggest that the effects of warm katabatic winds in the Po Valley (Italy) can indeed be detected in the increase of car accidents