A unified approach to nonlinearity, structural change and outliers

This paper demonstrates that the class of conditionally linear and Gaussianstate-space models offers a general and convenient framework for simultaneouslyhandling nonlinearity, structural change and outliers in time series. Manypopular nonlinear time series models, including threshold, smooth transitionand Markov-Switching models, can be written in state-space form. It is thenstraightforward to add components that capture parameter instability andintervention effects. We advocate a Bayesian approach to estimation andinference, using an efficient implementation of Markov Chain Monte Carlosampling schemes for such linear dynamic mixture models. The general modellingframework and the Bayesian methodology are illustrated by means of severalexamples. An application to quarterly industrial production growth rates forthe G7 countries demonstrates the empirical usefulness of the approach.Bayesian inference;threshold models;Markov-switching models;business cycle asymmetry;state-space models

Market frictions in entrepreneurial innovation: Theory and evidence

We propose a model of entrepreneurial innovation that rationalizes its pattern of boom and bust. In the model, a successful entrepreneurial project is the result of a search and matching process between entrepreneurs and capitalists. A strategic complementarity between the entrepreneurs\u2019 demand for funds and the capitalists\u2019 supply arises both on the extensive and on the intensive margin. Using data from the Global Entrepreneurship Monitor, and collecting data on the venture capital market of 23 OECD countries plus China for the period 2007\u20132015, we find robust evidence of complementarity across the two sides of the market. We also provide a quantitative estimate of a multiplier effect originating from such complementarity

Candecomp/Parafac with zero constraints at arbitrary positions in a loading matrix

When one interprets Candecomp/Parafac (CP) solutions for analyzing three-way data, small loadings are often ignored, that is, considered to be zero. Rather than just considering them zero, it seems better to actually model such values as zero. This can be done by successive modeling approaches as well as by a simultaneous modeling approach. This paper offers algorithms for three such approaches, and compares them on the basis of empirical data and a simulation study. The conclusion of the latter was that, under realistic circumstances, all approaches recovered the underlying structure well, when the number of values to constrain to zero was given. Whereas the simultaneous modeling approach seemed to perform slightly better, differences were very small and not substantial. Given that the simultaneous approach is far more time consuming than the successive approaches, the present study suggests that for practical purposes successive approaches for modeling zeros in the CP model seem to be indicated

Intercomparison of oceanic and atmospheric forced and coupled mesoscale simulations <br>Part I: Surface fluxes

International audienceA mesoscale non-hydrostatic atmospheric model has been coupled with a mesoscale oceanic model. The case study is a four-day simulation of a strong storm event observed during the SEMAPHORE experiment over a 500 × 500 km2 domain. This domain encompasses a thermohaline front associated with the Azores current. In order to analyze the effect of mesoscale coupling, three simulations are compared: the first one with the atmospheric model forced by realistic sea surface temperature analyses; the second one with the ocean model forced by atmospheric fields, derived from weather forecast re-analyses; the third one with the models being coupled. For these three simulations the surface fluxes were computed with the same bulk parametrization. All three simulations succeed well in representing the main oceanic or atmospheric features observed during the storm. Comparison of surface fields with in situ observations reveals that the winds of the fine mesh atmospheric model are more realistic than those of the weather forecast re-analyses. The low-level winds simulated with the atmospheric model in the forced and coupled simulations are appreciably stronger than the re-analyzed winds. They also generate stronger fluxes. The coupled simulation has the strongest surface heat fluxes: the difference in the net heat budget with the oceanic forced simulation reaches on average 50 Wm-2 over the simulation period. Sea surface-temperature cooling is too weak in both simulations, but is improved in the coupled run and matches better the cooling observed with drifters. The spatial distributions of sea surface-temperature cooling and surface fluxes are strongly inhomogeneous over the simulation domain. The amplitude of the flux variation is maximum in the coupled run. Moreover the weak correlation between the cooling and heat flux patterns indicates that the surface fluxes are not responsible for the whole cooling and suggests that the response of the ocean mixed layer to the atmosphere is highly non-local and enhanced in the coupled simulation

A unified approach to nonlinearity, structural change and outliers

This paper demonstrates that the class of conditionally linear and Gaussian state-space models offers a general and convenient framework for simultaneously handling nonlinearity, structural change and outliers in time series. Many popular nonlinear time series models, including threshold, smooth transition and Markov-Switching models, can be written in state-space form. It is then straightforward to add components that capture parameter instability and intervention effects. We advocate a Bayesian approach to estimation and inference, using an efficient implementation of Markov Chain Monte Carlo sampling schemes for such linear dynamic mixture models. The general modelling framework and the Bayesian methodology are illustrated by means of several examples. An application to quarterly industrial production growth rates for the G7 countries demonstrates the empirical usefulness of the approach

A study of longitudinal mobile health data through fuzzy clustering methods for functional data: The case of allergic rhinoconjunctivitis in childhood

The use of mobile communication devices in health care is spreading worldwide. A huge amount of health data collected by these devices (mobile health data) is nowadays available. Mobile health data may allow for real-time monitoring of patients and delivering ad-hoc treatment recommendations. This paper aims at showing how this may be done by exploiting the potentialities of fuzzy clustering techniques. In fact, such techniques can be fruitfully applied to mobile health data in order to identify clusters of patients for diagnostic classification and cluster-specific therapies. However, since mobile health data are full of noise, fuzzy clustering methods cannot be directly applied to mobile health data. Such data must be denoised prior to analyzing them. When longitudinal mobile health data are available, functional data analysis represents a powerful tool for filtering out the noise in the data. Fuzzy clustering methods for functional data can then be used to determine groups of patients. In this work we develop a fuzzy clustering method, based on the concept of medoid, for functional data and we apply it to longitudinal mHealth data on daily symptoms and consumptions of anti-symptomatic drugs collected by two sets of patients in Berlin (Germany) and Ascoli Piceno (Italy) suffering from allergic rhinoconjunctivitis. The studies showed that clusters of patients with similar changes in symptoms were identified opening the possibility of precision medicine

Effect of phytoremediated port sediment as an agricultural medium for pomegranate cultivation: Mobility of contaminants in the plant

Although the dredging of ports is a necessary management activity, it generates immense quantities of sediments, that are defined by the European Union as residues. On the other hand, the relevant peat demand for plant cultivation compromises its availability worldwide. In this context, the present work wanted to find an alternative substrate in order to replace and/or reduce the use of peat in agriculture, through the study of the suitability, concerning the exchange of substrate–plant–water pollutants, of the dredged remediated sediments as a fruit-growing media. Forty-five pomegranate trees (Punica granatum L. cv “Purple Queen”) were cultivated in three types of substrates (100% peat as a control, 100% dredged remediated sediments and 50% both mixed). The metal ion content and pesticide residues were analysed in the different plant parts (root, stem, leaves and fruits) and in drainage water. The results showed a limited transfer of pollutants. All the pollutants were below the legal limits, confirming that the dredged sediments could be used as a growing media, alone or mixed with other substrates. Thus, the results point out the need to open a European debate on the reuse and reconsideration of this residue from a circular economy point of view

Comparing home and parcel lockers’ delivery systems: a math-heuristic approach

E-commerce is a continuously growing sector worldwide, with important repercussions on the delivery system in urban area and especially in the Business to Consumer (B2C) sector. The delivery of a package to a consumer's address involves not only high costs for couriers (greater number of kilometres travelled), but also increased congestion and greater environmental pollution (greater volume of pollutants released into the air). To rationalize deliveries in urban areas the use of collection points, equipped with lockers, to store the goods that users have ordered has been considered in literature. This work compares two alternative delivery options: deliveries to the consumer's home versus to Lockers. To make this comparison we used a cluster first route second math-heuristic approach. In the clustering phase, we experimented a new clustering function, while the routing phase consists in solving an instance of the Traveling Salesman Problem for each generated cluster. Finally, we applied the math-heuristic to a real case (the Italian municipality of Dolo near Venice) and compared the two delivery alternatives. We evaluate the performance considering two different fleets of vehicles, with small and medium capacity. In addition, since additional trips might be performed by consumers to pick up parcels at Lockers, a sensitivity analysis was carried out to analyse the sustainability of the proposed city logistics scheme