Estimating end-use demand: A Bayesian approach

Eliminating negative end-use or appliance consumption estimates and incorporating direct metering information into the process of generating these estimates; these are two important aspects, of conditional demand analysis (CDA) that will be the focus of this raper. In both cases a Bayesian approach seems a natural way of proceeding. What needs to be investigated is whether it is also a viable and effective approach. In addition, such a framework naturally lends itself to prediction. Our application involves the estimation of electrical appliance consumptions for a sample of Australian households. This application is designed to illustrate the viability of a full Bayesian analysis of the problem

Estimating end-use demand: A Bayesian approach.

Eliminating negative end-use or appliance consumption estimates and incorporating direct metering information into the process of generating these estimates; these are two important aspects, of conditional demand analysis (CDA) that will be the focus of this raper. In both cases a Bayesian approach seems a natural way of proceeding. What needs to be investigated is whether it is also a viable and effective approach. In addition, such a framework naturally lends itself to prediction. Our application involves the estimation of electrical appliance consumptions for a sample of Australian households. This application is designed to illustrate the viability of a full Bayesian analysis of the problem.End-use demand; Direct metering; Non-negative estimates; Bayesian conditional demand analysis;

SuperJunction cascode, a configuration to break the silicon switching frequency limit

This paper evaluates the SuperJunction MOSFET in cascode configuration with a low-voltage silicon MOSFET. The structure combines the good switching performance provided by the cascode configuration with advantages of the silicon technology as the robustness, the maturity and the low-cost. The objective of this paper is to elucidate and to demonstrate the reduction of switching losses of SuperJunction MOSFETs in cascode configuration with respect to their standalone counterparts (directly driven). A detailed simulation analysis of power loss contributions is carried out under hard-switching operation. Eventually, experimental evidence is provided by using a boost converter (100 V-to-400 V) in continuous conduction mode for a wide range of switching frequency (100 kHz-to-400 kHz) and output power (180W-to-500W).This work has been supported by the Spanish Government under Project MINECO-13-DPI2013-47176-C2-2-R, MINECO-15-DPI2014-56358-JIN, the scholarship FPU14/03268 and the Principality of Asturias under the grants “Severo Ochoa” BP14-140 and by the Project FC-15- GRUPIN14-143 and by European Regional Development Fund (ERDF) grants

On the criticality of inferred models

Advanced inference techniques allow one to reconstruct the pattern of interaction from high dimensional data sets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to a phase transition. On one side, we show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher Information) is directly related to the model's susceptibility. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. On the other, this region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time-scales naturally yield models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA