Classical novae from the POINT-AGAPE microlensing survey of M31 - II. Rate and statistical characteristics of the nova population

The POINT-AGAPE (Pixel-lensing Observations with the Isaac Newton Telescope-Andromeda Galaxy Amplified Pixels Experiment) survey is an optical search for gravitational microlensing events towards the Andromeda galaxy (M31). As well as microlensing, the survey is sensitive to many different classes of variable stars and transients. In our first paper of this series, we reported the detection of 20 classical novae (CNe) observed in Sloan r' and i' passbands.

A statistical analysis of circumstellar material in Type Ia supernovae

A key tracer of the elusive progenitor systems of Type Ia supernovae (SNe Ia) is the detection of narrow blueshifted time-varying Na I D absorption lines, interpreted as evidence of circumstellar material surrounding the progenitor system. The origin of this material is controversial, but the simplest explanation is that it results from previous mass-loss in a system containing a white dwarf and a non-degenerate companion star. We present new single-epoch intermediate-resolution spectra of 17 low-redshift SNe Ia taken with XShooter on the European Southern Observatory Very Large Telescope. Combining this sample with events from the literature, we confirm an excess (∼20 per cent) of SNe Ia displaying blueshifted narrow Na I D absorption features compared to redshifted Na I D features. The host galaxies of SNe Ia displaying blueshifted absorption profiles are skewed towards later-type galaxies, compared to SNe Ia that show no Na I D absorption and SNe Ia displaying blueshifted narrow Na I D absorption features have broader light curves. The strength of the Na I D absorption is stronger in SNe Ia displaying blueshifted Na I D absorption features than those without blueshifted features, and the strength of the blueshifted Na I D is correlated with the B − V colour of the SN at maximum light. This strongly suggests the absorbing material is local to the SN. In the context of the progenitor systems of SNe Ia, we discuss the significance of these findings and other recent observational evidence on the nature of SN Ia progenitors. We present a summary that suggests that there are at least two distinct populations of normal, cosmologically useful SNe Ia.

A statistical analysis of person–to–vehicle communications channels in an urban environment at 5.8 GHz

In recent years, the embracement of smart devices carried or worn by people have transformed how society interact with one another. This trend has also been observed in the advancement of vehicular networks. Here, developments in wireless technologies for vehicle-to-vehicle (V2V) and vehicle-to-roadside (V2R) communications are leading to a new generation of vehicular networks. A natural extension of both types of networks will be their eventual wireless integration. Both people and vehicles will undoubtedly form integral parts of future mobile networks of people and things. Central to this will be the person-to-vehicle (P2V) communications channel. As the P2V channel will be subject to different signal propagation characteristics than either type of communication system considered in isolation, it is imperative the characteristics of the wireless channel must first be fully understood. To the best of the author's knowledge, this is a topic which has not yet been addressed in the open literature. In this paper we will present our most recent research on the statistical characterization of the 5.8 GHz person-to-vehicle channel in an urban environment.

A statistical characterization of on–body fading using the shadowed k–µ fading model

In this paper we investigate the received signal characteristics of on-body communications channels at 2.45 GHz. The hypothetical body area network configuration considered a transmitter node situated on the person’s left waist and receiving nodes positioned on the head, knee and wrist of the person’s right side. The on-body channel measurements were performed in both anechoic and reverberant environments while the person was moving. It was found that the recently proposed shadowed κ‒μ fading model provided an excellent fit to the measured data.

Indoor off–body communications at 5.8 GHz with multiple antennas at the base station: a statistical characterization using the Nakagami–m fading model

In this paper we investigate the first and second order characteristics of the received signal at the output ofhypothetical selection, equal gain and maximal ratio combiners which utilize spatially separated antennas at the basestation. Considering a range of human body movements, we model the model the small-scale fading characteristics ofthe signal using diversity specific analytical equations which take into account the number of available signal branchesat the receiver. It is shown that these equations provide an excellent fit to the measured channel data. Furthermore, formany hypothetical diversity receiver configurations, the Nakagami-m parameter was found to be close to 1.

Statistical Tests for Joint Analysis of Performance Measures

Recently there has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and architectural complexity). Once one has learned a model based on their devised method, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Unfortunately, the standard tests used for this purpose are not able to jointly consider performance measures. The aim of this paper is to resolve this issue by developing statistical procedures that are able to account for multiple competing measures at the same time. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameter of such models, as usually the number of studied cases is very reduced in such comparisons. Real data from a comparison among general purpose classifiers is used to show a practical application of our tests.

Forecasting Methodologies for Ganoderma Spore Concentration Using Combined Statistical Approaches and Model Evaluations

High concentration levels of Ganoderma spp. spores were observed in Worcester, UK, during 2006–2010.These basidiospores are known to cause sensitization due to the allergen content and their small dimensions. This enables them to penetrate the lower part of the respiratory tract in humans. Establishment of a link between occurring symptoms of sensitization to Ganoderma spp. and other basidiospores is challenging due to lack of information regarding spore concentration in the air. Hence, aerobiological monitoring should be conducted, and if possible extended with the construction of forecast models. Daily mean concentration of allergenic Ganoderma spp. spores in the atmosphere of Worcester was measured using 7-day volumetric spore sampler through five consecutive years. The relationships between the presence of spores in the air and the weather parameters were examined. Forecast models were constructed for Ganoderma spp. spores using advanced statistical techniques, i.e. multivariate regression trees and artificial neural networks. Dew point temperature along with maximumtemperature was the most important factor influencing the presence of spores in the air of Worcester. Based on these two major factors and several others of lesser importance, thresholds for certain levels of fungal spore concentration, i.e. low (0–49 s m−3), moderate(50–99 s m−3), high (100–149 s m−3) and very high (150

The Double Pareto-Lognormal Distribution and its applications in actuarial science and finance

Le but de ce mémoire de maîtrise est de décrire les propriétés de la loi double Pareto-lognormale, de montrer comment on peut introduire des variables explicatives dans le modèle et de présenter son large potentiel d'applications dans le domaine de la science actuarielle et de la finance. Tout d'abord, nous donnons la définition de la loi double Pareto-lognormale et présentons certaines de ses propriétés basées sur les travaux de Reed et Jorgensen (2004). Les paramètres peuvent être estimés en utilisant la méthode des moments ou le maximum de vraisemblance. Ensuite, nous ajoutons une variable explicative à notre modèle. La procédure d'estimation des paramètres de ce mo-\\dèle est également discutée. Troisièmement, des applications numériques de notre modèle sont illustrées et quelques tests statistiques utiles sont effectués.

Statistical Inference for Some Measures of System Availability

Department of Statistics, Cochin University of Science and Technology

Statistical signal extraction using stable processes

The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation.