Efficient High-Dimensional Importance Sampling

The paper describes a simple, generic and yet highly accurate Efficient Importance Sampling (EIS) Monte Carlo (MC) procedure for the evaluation of high-dimensional numerical integrals. EIS is based upon a sequence of auxiliary weighted regressions which actually are linear under appropriate conditions. It can be used to evaluate likelihood functions and byproducts thereof, such as ML estimators, for models which depend upon unobservable variables. A dynamic stochastic volatility model and a logit panel data model with unobserved heterogeneity (random effects) in both dimensions are used to provide illustrations of EIS high numerical accuracy, even under small number of MC draws. MC simulations are used to characterize the finite sample numerical and statistical properties of EIS-based ML estimators.

Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models

In this paper, Efficient Importance Sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as well as simulation smoothing where the latent volatilities are sampled at once. Based on this EIS simulation smoother a Bayesian Markov Chain Monte Carlo (MCDC) posterior analysis of the parameters of SV models can be performed.

Learning to automatically detect features for mobile robots using second-order Hidden Markov Models

In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T-intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.Comment: 200

Economic Development, Legality, and the Transplant Effect

We analyze the determinants of effective legal institutions (legality) using data from 49 countries. We show that the way the law was initially transplanted and received is a more important determinant than the supply of law from a particular legal family. Countries that have developed legal orders internally, adapted the transplanted law, and/or had a population that was already familiar with basic principles of the transplanted law have more effective legality than countries that received foreign law without any similar pre-dispositions. The transplanting process has a strong indirect effect on economic development via its impact on legality.http://deepblue.lib.umich.edu/bitstream/2027.42/39692/3/wp308.pd

Economic Development, Legality, and the Transplant Effect

We analyze the determinants of effective legal institutions (legality) using data from 49 countries. We show that the way the law was initially transplanted and received is a more important determinant than the supply of law from a particular legal family. Countries that have developed legal orders internally, adapted the transplanted law, and/or had a population that was already familiar with basic principles of the transplanted law have more effective legality than countries that received foreign law without any similar pre-dispositions. The transplanting process has a strong indirect effect on economic development via its impact on legality.transplant versus origin, receptive, unreceptive, direct and indirect transplants, legality

Economic Development, Legality, and the Transplant Effect

We analyze the determinants of effective legal institutions (legality) using data from 49 countries. We show that the way the law was initially transplanted and received is a more important determinant than the supply of law from a particular legal family. Countries that have developed legal orders internally, adapted the transplanted law, and/or had a population that was already familiar with basic principles of the transplanted law have more effective legality than countries that received foreign law without any similar pre-dispositions. The transplanting process has a strong indirect effect on economic development via its impact on legality.legal transplants, legal families, legality, effectiveness of legal institutions, economic development

Bayesian Analysis of a Probit Panel Data Model with Unobserved Individual Heterogeneity and Autocorrelated Errors

In this paper, we perform Bayesian analysis of a panel probit model with unobserved individual heterogeneity and serially correlated errors. We augment the data with latent variables and sample the unobserved heterogeneity component as one Gibbs block per individual using a flexible piecewise linear approximation to the marginal posterior density. The latent time effects are simulated as another Gibbs block. For this purpose we develop a new user-friendly form of the Efficient Importance Sampling proposal density for an Acceptance-Rejection Metropolis-Hastings step. We apply our method to the analysis of product innovation activity of a panel of German manufacturing firms in response to imports, foreign direct investment and other control variables. The dataset used here was analyzed under more restrictive assumptions by Bertschek and Lechner (1998) and Greene (2004). Although our results differ to a certain degree from these benchmark studies, we confirm the positive effect of imports and FDI on firms' innovation activity. Moreover, unobserved firm heterogeneity is shown to play a far more significant role in the application than the latent time effects.Dynamic latent variables; Markov Chain Monte Carlo; importance sampling

A Systematic Approach to Incremental Redundancy over Erasure Channels

As sensing and instrumentation play an increasingly important role in systems controlled over wired and wireless networks, the need to better understand delay-sensitive communication becomes a prime issue. Along these lines, this article studies the operation of data links that employ incremental redundancy as a practical means to protect information from the effects of unreliable channels. Specifically, this work extends a powerful methodology termed sequential differential optimization to choose near-optimal block sizes for hybrid ARQ over erasure channels. In doing so, an interesting connection between random coding and well-known constants in number theory is established. Furthermore, results show that the impact of the coding strategy adopted and the propensity of the channel to erase symbols naturally decouple when analyzing throughput. Overall, block size selection is motivated by normal approximations on the probability of decoding success at every stage of the incremental transmission process. This novel perspective, which rigorously bridges hybrid ARQ and coding, offers a pragmatic means to select code rates and blocklengths for incremental redundancy.Comment: 7 pages, 2 figures; A shorter version of this article will appear in the proceedings of ISIT 201

Eigenvalue amplitudes of the Potts model on a torus

29 pages, 4 figuresInternational audienceWe consider the Q-state Potts model in the random-cluster formulation, defined on finite two-dimensional lattices of size L x N with toroidal boundary conditions. Due to the non-locality of the clusters, the partition function Z(L,N) cannot be written simply as a trace of the transfer matrix T_L. Using a combinatorial method, we establish the decomposition Z(L,N) = \sum_{l,D_k} b^{l,D_k} K_{l,D_k}, where the characters K_{l,D_k} = \sum_i (\lambda_i)^N are simple traces. In this decomposition, the amplitudes b^{l,D_k} of the eigenvalues \lambda_i of T_L are labelled by the number l=0,1,...,L of clusters which are non-contractible with respect to the transfer (N) direction, and a representation D_k of the cyclic group C_l. We obtain rigorously a general expression for b^{l,D_k} in terms of the characters of C_l, and, using number theoretic results, show that it coincides with an expression previously obtained in the continuum limit by Read and Saleur