On the Use of Running Trends as Summary Statistics for Univariate Time Series and Time Series Association

Given a time series, running trends analysis (RTA) involves evaluating least squares trends over overlapping time windows of L consecutive time points, with overlap by all but one observation. This produces a new series called the “running trends series,” which is used as summary statistics of the original series for further analysis. In recent years, RTA has been widely used in climate applied research as summary statistics for time series and time series association. There is no doubt that RTA might be a useful descriptive tool, but, despite its general use in applied research, precisely what it reveals about the underlying time series is unclear and, as a result, its interpretation is unclear too. This paper contributes to such interpretation in two ways: 1) an explicit formula is obtained for the set of time series with a given series of running trends, making it possible to show that running trends, alone, perform very poorly as summary statistics for univariate time series and time series association; and 2) an equivalence is established between RTA and the estimation of a (possibly nonlinear) trend component of the underlying time series using a weighted moving average filter. Such equivalence provides a solid ground for RTA implementation and interpretation/validation. In this respect, the authors propose as diagnostic tools for RTA 1) the plot of the original series, with RTA trend estimation superposed, 2) the average R2 value and the percentage of statistically significant running trends across windows, and 3) the plot of the running trends series with the corresponding confidence intervals.This work has been supported by Projects CGL2010-12153-E and AYA2010-22039-C02-01 from the Spanish Department of Science and Innovation (MICINN)

Water transport among the world ocean basins within the water cycle

The global water cycle involves water-mass transport on land, in the atmosphere, in the ocean, and among them. Quantification of such transport, especially its time evolution, is essential to identify the footprints of climate change, and it also helps to constrain and improve climatic models. In the ocean, net water-mass transport among the ocean basins is a key process, but it is currently a poorly estimated parameter. We propose a new methodology that incorporates the time-variable gravity observations from the Gravity Recovery and Climate Experiment (GRACE) satellite (2003–2016) to estimate the change in water content; this new approach also overcomes some fundamental limitations of existing methods. We show that the Pacific and Arctic oceans receive an average of 1916 (95 % confidence interval of [1812, 2021]) Gt per month (∼0.72±0.02 Sv) of excess freshwater from the atmosphere and the continents that is discharged into the Atlantic and Indian oceans, where net evaporation minus precipitation returns the water to complete the cycle. This is in contrast to previous GRACE-based studies, where the notion of a see-saw mass exchange between the Pacific and the Atlantic and Indian oceans has been reported. Seasonal climatology as well as the interannual variability of water-mass transport are also reported.This research has been supported by the Spanish Ministry of Science, Innovation and Universities (grant no. RTI2018-093874-B-100)

A modelling approach to optimal imperfect maintenance of repairable equipment with multiple failure modes

Most of the existing works on optimal imperfect maintenance activities of a repairable equipment with independent components consider a single model for equipment behaviour. In addition, it is assumed that all the components of the equipment share the same model and the same maintenance intervals and that effectiveness of maintenance is known. In this paper we take a different approach. In order to formalize the uncertainty on the occurrence of failures and on the effect of maintenance activities, we consider, for each component, a class of candidate models. These models are obtained by combining failure rate models with imperfect maintenance models. The best model, that might be different for the different components, is then selected. All the parameters are assumed to be unknown and are jointly estimated via maximum likelihood. Model selection is performed, separately for each component, using standard selection criteria that take the problem of over-parametrization into account. The selected models are used to derive the cost per time unit and the average reliability of the equipment, the objective functions of a Multi-Objective Optimization Problem with maintenance intervals of each single component as decision variables. The proposed procedure is illustrated using a real data example.This work was a collaborative effort and was partly supported by the Conselleria d’Educació, Investigació, Cultura i Sport (Generalitat de la Comunitat Valenciana, Spain) under grant GV/2017/015

Effects of seawater ingestion on lactate response to exercise in runners

The aim of this study was to examine the effect of microfiltered and sterilized seawater ingestion on running performance in a hot environment. This cross-over, double-blind randomized trial included 12 experienced male runners. The subjects randomly consumed seawater (SW) or pure water (placebo) in an equivalent amount of 50 ml five minutes prior to running at 40% of their VO2 max for 95.0 ± 18.5 min, at 30°C, until they lost 3% of body weight. Every 20 minutes, a measurement of their body weight was taken and a blood lactate analysis was performed. The concentration of lactate was significantly lower after the running exercise in the SW condition compared to placebo. The results of this study suggest the ergogenic effects of microfiltered and sterilized seawater ingestion on running performance and lactate production

Mediterranean Surface Geostrophic Circulation from Satellite Gravity and Altimetry Observations

We present a data-based approach to study the mean and the climatology of the surface geostrophic currents (SGC) for the Mediterranean Sea, using satellite ocean surface altimetry observations for 22 years (1993–2014) in conjunction with the geoid solution derived from the space mission of GOCE (gravity field and steady-state ocean circulation explorer; Release 4). The resultant product is the Mediterranean SGC velocity field, that we denote by SGCGOCE−Alt, given in spatial resolution of 1/4∘ and monthly time resolution. It exhibits smaller scales and lower dynamic intensities in comparison with open oceans, making the Mediterranean Sea a challenging test case for our satellite-based analysis. The mean SGCGOCE−Alt is largely consistent with previous findings but with additional circulation features in time and space. We also compare our results with the SGC output from the regional hydrodynamic model of Mercator that assimilates satellite altimetry, satellite sea surface temperature, and in situ observations. The prominent SGC features agree well not only on the large and subbasin scales but also in the widespread mesoscale dynamics. We find, however, comparatively lower intensities than the Mercator model in general, with differences that are on average around 7 cm/s, but might reach 13 cm/s in some coastal areas.The work is supported by Taiwan MoST Grant #105-2811-M-001-031. M. Dolores Sempere is supported by the PhD Grant UAFPU2014-5884 from the University of Alicante

Assessing the Predictive Performance of Probabilistic Caries Risk Assessment Models: The Importance of Calibration

Probabilistic caries risk assessment models (P-CRA), such as the Cariogram, are promising tools to planning treatments in order to control and prevent caries. The usefulness of these models for informing patients and medical decision-making depends on 2 properties known as discrimination and calibration. Current common assessment of P-CRA models, however, ignores calibration, and this can be misleading. The aim of this paper was to provide tools for a proper assessment of calibration of the P-CRA models and improve calibration when lacking. A combination of standard calibration tools (calibration plot, calibration in-the-large, and calibration slope) and 3 novel measures of calibration (the Calibration Index and 2 related metrics, E50 and E90) are proposed to evaluate if a P-CRA model is well calibrated. Moreover, an approach was proposed and validated using data from a previous follow-up study performed on children evaluated by means of a reduced Cariogram model; Platt scaling and isotonic regression were applied showing a lack of calibration. The use of the Cariogram overestimates the actual risk of new caries for forecast probabilities 0.6. Both Platt scaling and isotonic regression were able to significantly improve the calibration of the reduced Cariogram model, preserving its discrimination properties. The average specificity and sensitivity for both Platt scaling and isotonic regression using the cut-off point p= 0.5 were >83 and their sum well exceeded 160. The benefits of the proposed calibration methods are promising, but further research in this field is required

Oral Health Status of Children with Autism in Central Italy

Children with autism spectrum disorder (ASD) have significantly higher prevalence and caries severity compared to the average population. Knowledge about the oral health indices of children with this mental disorder is key to designing efficient plans of intervention. This paper reports the results of a study on the oral health status of children with ASD in central Italy. This is the first study of this type in Italy. The sample consists of 229 autistic children aged between 5 and 14 years, attending the Unit of Special Needs Policlinico Umberto I in Rome. Each patient received an intraoral examination to investigate decayed, missing, and filled teeth as well as periodontal status. Information on demographic attributes, dietary habits, medical history, and child’s cooperativeness at the first visit was also recorded. Of the participants, 79.26% presented signs of gingivitis and about 90% of them had plaque. Caries prevalence was 66.38%. The average of the total number of decayed, missing, and filled teeth in the permanent and primary dentition was 2.91. Among the factors considered, only dietary habits and the periodontal indices showed statistically significant association with caries prevalence and caries severity. Despite the selection bias, that prevents us to interpret the results presented as epidemiological evidence, our study suggests that children with ASD in central Italy represent a population at risk.The work was supported by the Department of Oral and Maxillo-Facial Science, Pediatric Dentistry Unit, Policlinico Umberto I, Rome, Italy

A decision-theoretic approach to data disclosure problems

This paper presents a decision-theoretic approach to data disclosure problems. The approach is innovative because (i) it offers a theoretical framework to develop optimality criteria for the choice of the best form of data release, (ii) it recognizes the different perspectives of the statistical agency and of the users of the data in assessing the extent of disclosure and the quality of the users ’ inference associated with different forms of data release. This leads to new measures of disclosure risk and data utility that take into account not only what the users believe they have learned from the data, but also to what extent their inferences are correct

Un criterio predittivo generalizzato per la scelta tra modelli

Dottorato di ricerca in statistica metodologica. 11. cicloConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7, Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

A generalized predictive criterion for model selection

Given a random sample from some unknown model belonging to a finite class of parametric models, assume that the estimate of the density of a future observation is of interest. San Martini & Spezzaferri (1984) proposed for this problem a predictive criterion based on the logarithmic utility function. The present authors investigate a generalization of this criterion that uses as a loss function an element of the class of alpha-divergences discussed by Ali & Silvey (1966) and Csiszar (1967). They also discuss briefly the case in which the class of models considered is not exhaustive