Generalized low-density codes with BCH constituents for full-diversity near-outage performance

A new graph-based construction of generalized low density codes (GLD-Tanner) with binary BCH constituents is described. The proposed family of GLD codes is optimal on block erasure channels and quasi-optimal on block fading channels. Optimality is considered in the outage probability sense. Aclassical GLD code for ergodic channels (e.g., the AWGN channel,the i.i.d. Rayleigh fading channel, and the i.i.d. binary erasure channel) is built by connecting bitnodes and subcode nodes via a unique random edge permutation. In the proposed construction of full-diversity GLD codes (referred to as root GLD), bitnodes are divided into 4 classes, subcodes are divided into 2 classes, and finally both sides of the Tanner graph are linked via 4 random edge permutations. The study focuses on non-ergodic channels with two states and can be easily extended to channels with 3 states or more.

Quasi-integration in less-than-truckload trucking

This work studies the organization of less-than-truckload trucking from a contractual point of view. We show that the huge number of owner-operators working in the industry hides a much less fragmented reality. Most of those owner-operators are quasi-integrated in higher organizational structures. This hybrid form is generally more efficient than vertical integration because, in the Spanish institutional environment, it lessens serious moral hazard problems, related mainly to the use of the vehicles, and makes it possible to reach economies of scale and density. Empirical evidence suggests that what leads organizations to vertically integrate is not the presence of such economies but hold-up problems, related to the existence of specific assets. Finally, an international comparison hints that institutional constraints are able to explain differences in the evolution of vertical integration across countries.

Testing for convergence clubs in income per-capita: A predictive density approach

The paper proposes a technique to jointly test for groupings of unknown size in the cross sectional dimension of a panel and estimates the parameters of each group, and applies it to identifying convergence clubs in income per-capita. The approach uses the predictive density of the data, conditional on the parameters of the model. The steady state distribution of European regional data clusters around four poles of attraction with different economic features. The distribution of incomeper-capita of OECD countries has two poles of attraction and each grouphas clearly identifiable economic characteristics.

Asymptotic behaviour of the density in a parabolic SPDE

Consider the density of the solution $X(t,x)$ of a stochastic heat equation with small noise at a fixed $t\in [0,T]$, $x \in [0,1]$.In the paper we study the asymptotics of this density as the noise is vanishing. A kind of Taylor expansion in powers of the noiseparameter is obtained. The coefficients and the residue of the expansion are explicitly calculated.In order to obtain this result some type of exponential estimates of tail probabilities of the difference between the approximatingprocess and the limit one is proved. Also a suitable local integration by parts formula is developped.

An experimental test of loss aversion and scale compatibility

This paper studies two important reasons why people violate procedure invariance, loss aversion and scale compatibility. The paper extends previous research on loss aversion and scale compatibility by studying loss aversion and scale compatibility simultaneously, by looking at a new decision domain, medical decision analysis, and by examining the effect of loss aversion and scale compatibility on "well-contemplated preferences." We find significant evidence both of loss aversion and scale compatibility. However, the sizes of the biases due to loss aversion and scale compatibility vary over trade-offs and most participants do not behave consistently according to loss aversion or scale compatibility. In particular, the effect of loss aversion in medical trade-offs decreases with duration. These findings are encouraging for utility measurement and prescriptive decision analysis. There appear to exist decision contexts in which the effects of loss aversion and scale compatibility can be minimized and utilities can be measured that do not suffer from these distorting factors.

Distributional equivalence and subcompositional coherence in the analysis of contingency tables, ratio-scale measurements and compositional data

We consider two fundamental properties in the analysis of two-way tables of positive data: the principle of distributional equivalence, one of the cornerstones of correspondence analysis of contingency tables, and the principle of subcompositional coherence, which forms the basis of compositional data analysis. For an analysis to be subcompositionally coherent, it suffices to analyse the ratios of the data values. The usual approach to dimension reduction in compositional data analysis is to perform principal component analysis on the logarithms of ratios, but this method does not obey the principle of distributional equivalence. We show that by introducing weights for the rows and columns, the method achieves this desirable property. This weighted log-ratio analysis is theoretically equivalent to spectral mapping , a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra. The close relationship between spectral mapping and correspondence analysis is also explained, as well as their connection with association modelling. The weighted log-ratio methodology is applied here to frequency data in linguistics and to chemical compositional data in archaeology.

A medium-scale open economy model of Australia

We estimate an open economy dynamic stochastic general equilibrium (DSGE)model of Australia with a number of shocks, frictions and rigidities, matching alarge number of observable time series. We find that both foreign and domesticshocks are important drivers of the Australian business cycle.We also find that theinitial impact on inflation of an increase in demand for Australian commoditiesis negative, due to an improvement in the real exchange rate, though there is apersistent positive effect on inflation that dominates at longer horizons.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

Geological and Geomorphological Cartography at Scale 1: 10.000: a Tool of Management for Towns

Geological and geomorphological mapping at scale 1:10.000 besides from being an important source of scientific information it is also a necessary tool for municipal organs in order to make proper decisions when dealing with geo-environmental problems concerning integral territorial development. In this work, detailed information is given on the contents of such maps, their social and economical application, and a balance of the investment and gains that derives from them

Small scale underwater change detection

In this paper, we present a method to deal with the constraints of the underwater medium for finding changes between sequences of underwater images. One of the main problems of underwater medium for automatically detecting changes is the low altitude of the camera when taking pictures. This emphasise the parallax effect between the images as they are not taken exactly at the same position. In order to solve this problem, we are geometrically registering the images together taking into account the relief of the scene