On the non-negative first-order exponential bilinear time series model

In this paper the bilinear model BL(1,0,1,1) driven by exponential distributed innovations is studied in some detail. Conditions under which the model is strictly stationary as well as some properties of the stationary distribution are discussed. Moreover, parameter estimation is also addressed. (C) 2005 Elsevier B.V. All rights reserved

Optimal alarm systems for count processes

In many phenomena described by stochastic processes, the implementation of an alarm system becomes fundamental to predict the occurrence of future events. In this work we develop an alarm system to predict whether a count process will upcross a certain level and give an alarm whenever the upcrossing level is predicted. We consider count models with parameters being functions of covariates of interest and varying on time. This article presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning the number of sunspot on the surface of the sun

Integer-valued autoregressive processes with periodic structure

In this paper the periodic integer-valued autoregressive model of order one with period T, driven by a periodic sequence of independent Poisson-distributed random variables, is studied in some detail. Basic probabilistic and statistical properties of this model are discussed. Moreover, parameter estimation is also addressed. Specifically, the methods of estimation under analysis are the method of moments, least squares-type and likelihood-based ones. Their performance is compared through a simulation study. (C) 2009 Elsevier B.V. All rights reserved

Optimal alarm systems for FIAPARCH processes

In this work, an optimal alarm system is developed to predict whether a financial time series modeled via Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) models, up/downcrosses some particular level and give an alarm whenever this crossing is predicted. The paper presents classical and Bayesian methodology for producing optimal alarm systems. Both methodologies are illustrated and their performance compared through a simulation study. The work finishes with an empirical application to a set of data concerning daily returns of the Sao Paulo Stock Market

Wavelet-Based Detection of Outliers in Poisson INAR(1) Time Series

The presence of outliers or discrepant observations has a negative impact in time series modelling. This paper considers the problem of detecting outliers, additive or innovational, single, multiple or in patches, in count time series modelled by first-order Poisson integer-valued autoregressive, PoINAR(1), models. To address this problem, two wavelet-based approaches that allow the identification of the time points of outlier occurrence are proposed. The effectiveness of the proposed methods is illustrated with synthetic as well as with an observed dataset

Modelling overdispersion with integer-valued moving average processes

A new first-order integer-valued moving average, INMA(1), model based on the negative binomial thinning operation defined by Risti´c et al. [21] is proposed and characterized. It is shown that this model has negative binomial (NB) marginal distribution when the innovations follow a NB distribution and therefore it can be used in situations where the data present overdispersion. Additionally, this model is extended to the bivariate context. The Generalized Method of Moments (GMM) is used to estimate the unknown parameters of the proposed models and the results of a simulation study that intends to investigate the performance of the method show that, in general, the estimates are consistent and symmetric. Finally, the proposed model is fitted to a real dataset and the quality of the adjustment is evaluated.publishe

Clinical chronobiology: a timely consideration in critical care medicine

A fundamental aspect of human physiology is its cyclical nature over a 24-h period, a feature conserved across most life on Earth. Organisms compartmentalise processes with respect to time in order to promote survival, in a manner that mirrors the rotation of the planet and accompanying diurnal cycles of light and darkness. The influence of circadian rhythms can no longer be overlooked in clinical settings; this review provides intensivists with an up-to-date understanding of the burgeoning field of chronobiology, and suggests ways to incorporate these concepts into daily practice to improve patient outcomes. We outline the function of molecular clocks in remote tissues, which adjust cellular and global physiological function according to the time of day, and the potential clinical advantages to keeping in time with them. We highlight the consequences of "chronopathology", when this harmony is lost, and the risk factors for this condition in critically ill patients. We introduce the concept of "chronofitness" as a new target in the treatment of critical illness: preserving the internal synchronisation of clocks in different tissues, as well as external synchronisation with the environment. We describe methods for monitoring circadian rhythms in a clinical setting, and how this technology may be used for identifying optimal time windows for interventions, or to alert the physician to a critical deterioration of circadian rhythmicity. We suggest a chronobiological approach to critical illness, involving multicomponent strategies to promote chronofitness (chronobundles), and further investment in the development of personalised, time-based treatment for critically ill patients

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Up, down, near, far: an online vestibular contribution to distance judgement

Whether a visual stimulus seems near or far away depends partly on its vertical elevation. Contrasting theories suggest either that perception of distance could vary with elevation, because of memory of previous upwards efforts in climbing to overcome gravity, or because of fear of falling associated with the downwards direction. The vestibular system provides a fundamental signal for the downward direction of gravity, but the relation between this signal and depth perception remains unexplored. Here we report an experiment on vestibular contributions to depth perception, using Virtual Reality. We asked participants to judge the absolute distance of an object presented on a plane at different elevations during brief artificial vestibular inputs. Relative to distance estimates collected with the object at the level of horizon, participants tended to overestimate distances when the object was presented above the level of horizon and the head was tilted upward and underestimate them when the object was presented below the level of horizon. Interestingly, adding artificial vestibular inputs strengthened these distance biases, showing that online multisensory signals, and not only stored information, contribute to such distance illusions. Our results support the gravity theory of depth perception, and show that vestibular signals make an on-line contribution to the perception of effort, and thus of distance