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Kernel density estimation (KDE) is a popular statistical technique for estimating the underlying density distribution with minimal assumptions. Although they can be shown to achieve asymptotic estimat...
Testing covariance structure is of significant interest in many areas of statistical analysis and construction of compressed sensing matrices is an important problem in signal processing. Motivated b...
It has long been recognized that a country's tariffs are the endogenous outcome of a rent-seeking game whose equilibrium reflects national institutions. Thus, the structure of tariffs across industrie...
Whether the composition of industrial activity influences innovation is the key question of this paper. The analysis is based on a model that integrates different kinds of diversity measures aiming ...
An important decision that multinational firms (MNFs) face when expanding abroad concerns the specific form of their investment. The usual choice is between exports, licensing or franchising, and fo...
We examine how the legal protection of outside shareholders and the appropriative costs that they induce influence the incentives for private firms to go public.A higher degree of protection of shareh...
This paper is concerned with the set of mutual relationships between firm valuation and investment, and with the possible endogeneity of ownership structure. In order to deal with them properly, we a...
In this paper, three points are argued. The first is that Ronald Coase, best known as the forefather of transaction cost theory, foresaw many of the critical questions that proponents of the resourceb...
The estimation of Bayesian networks given high-dimensional data sets, in particular given gene expression data sets, has been the focus of much recent research. While there are many methods availabl...
Statistical inference for stochastic processes with time-varying spectral characteristics has received considerable attention in recent decades.We develop a nonparametric test for stationarity again...
We discuss the optimal design problem in regression models with long-range dependence error structure. Asymptotic optimal designs are derived and it is demonstrated that these designs depend only in...
This study introduces a new method of visualizing complex tree structured objects. The usefulness of this method is illustrated in the context of detecting unexpected features in a data set of very ...
Deep belief networks are a powerful way to model complex probability distributions. However, learning the structure of a belief network, particularly one with hidden units, is difficult. The Indian...
The organizational structure of Embraer's EMBRAER 170/190 Program has made it possible to integrate the efforts of thousands of people from many different countries and from different companies to th...
Nowadays, it is known that a part of the manufacturers in the agricultural machinery sector do not use reasoning techniques supporting their product design processes. It can be perceived that design u...

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