Essays on numerically efficient inference in nonlinear and non-Gaussian state space models, and commodity market analysis.

The first two articles build procedures to simulate vector of univariate states and estimate parameters in nonlinear and non Gaussian state space models. We propose state space speci fications that offer more flexibility in modeling dynamic relationship with latent variables. Our procedures are extension of the HESSIAN method of McCausland[2012]. Thus, they use approximation of the posterior density of the vector of states that allow to : simulate directly from the state vector posterior distribution, to simulate the states vector in one bloc and jointly with the vector of parameters, and to not allow data augmentation. These properties allow to build posterior simulators with very high relative numerical efficiency. Generic, they open a new path in nonlinear and non Gaussian state space analysis with limited contribution of the modeler. The third article is an essay in commodity market analysis. Private firms coexist with farmers' cooperatives in commodity markets in subsaharan african countries. The private firms have the biggest market share while some theoretical models predict they disappearance once confronted to farmers cooperatives. Elsewhere, some empirical studies and observations link cooperative incidence in a region with interpersonal trust, and thus to farmers trust toward cooperatives. We propose a model that sustain these empirical facts. A model where the cooperative reputation is a leading factor determining the market equilibrium of a price competition between a cooperative and a private firm

Bayesian inference and model comparison for random choice structures

We complete the development of a testing ground for axioms of discrete stochastic choice. Our contribution here is to develop new posterior simulation methods for Bayesian inference, suitable for a class of prior distributions introduced by McCausland and Marley (2013). These prior distributions are joint distributions over various choice distributions over choice sets of di fferent sizes. Since choice distributions over di fferent choice sets can be mutually dependent, previous methods relying on conjugate prior distributions do not apply. We demonstrate by analyzing data from a previously reported experiment and report evidence for and against various axioms.

Inference for nonparametric high-frequency estimators with an application to time variation in betas

We consider the problem of conducting inference on nonparametric high-frequency estimators without knowing their asymptotic variances. We prove that a multivariate subsampling method achieves this goal under general conditions that were not previously available in the literature. We suggest a procedure for a data-driven choice of the bandwidth parameters. Our simulation study indicates that the subsampling method is much more robust than the plug-in method based on the asymptotic expression for the variance. Importantly, the subsampling method reliably estimates the variability of the Two Scale estimator even when its parameters are chosen to minimize the finite sample Mean Squared Error; in contrast, the plugin estimator substantially underestimates the sampling uncertainty. By construction, the subsampling method delivers estimates of the variance-covariance matrices that are always positive semi-definite. We use the subsampling method to study the dynamics of financial betas of six stocks on the NYSE. We document significant variation in betas within year 2006, and find that tick data captures more variation in betas than the data sampled at moderate frequencies such as every five or twenty minutes. To capture this variation we estimate a simple dynamic model for betas. The variance estimation is also important for the correction of the errors-in-variables bias in such models. We find that the bias corrections are substantial, and that betas are more persistent than the naive estimators would lead one to believe.

Statistical Inference for Some Measures of System Availability

Department of Statistics, Cochin University of Science and Technology

Bayesian Inference in Exponential and Pareto populations in the presence of Outliers

This thesis Entitled Bayesian inference in Exponential and pareto populations in the presence of outliers. The main theme of the present thesis is focussed on various estimation problems using the Bayesian appraoch, falling under the general category of accommodation procedures for analysing Pareto data containing outlier. In Chapter II. the problem of estimation of parameters in the classical Pareto distribution specified by the density function. In Chapter IV. we discuss the estimation of (1.19) when the sample contain a known number of outliers under three different data generating mechanisms, viz. the exchangeable model. Chapter V the prediction of a future observation based on a random sample that contains one contaminant. Chapter VI is devoted to the study of estimation problems concerning the exponential parameters under a k-outlier model.

The role of NGO in informal seed production and dissemination: The case of eastern Ethiopia

Seed is the basic input to crop production. Farmer-based seed production as an alternative agricultural technology transfer is increasingly given especial attention in developing countries where food insecurity is critical. This paper aims to assess the seed production and dissemination strategy among smallholder farmers in eastern Ethiopia that has been introduced by Hararghe Catholic Secretariat (a Non-GovernmentalOrganization). A survey of 160 households in four administrative districts and focus group discussions were used to collect data. While narratives helped understand the process, logistic regressionwas used to identify determinants of land allocation to seed production. Results indicate the crucial role of informal networks and social capital as facilitators of access to production inputs, information and knowledge. The informal seed supply system initiated by the NGO has a huge potential to benefit smallholder farmers by improving their access to higher-yielding varieties of various crops, thereby contributing to an increase in their wellbeing. However, the traditional practice of seed exchange, influenced by social relations, will remain uneconomical to seed producers. Thus, the paper suggests that this potential can be further exploited if some preconditions such as establishment of seed banks, investment in human capital, removal of the underlying constraints and creation of reliable seed markets are given emphasis.

A Theory of Quantitative Inference Applied to a Mechanical Design Compiler

This thesis presents the ideas underlying a computer program that takes as input a schematic of a mechanical or hydraulic power transmission system, plus specifications and a utility function, and returns catalog numbers from predefined catalogs for the optimal selection of components implementing the design. Unlike programs for designing single components or systems, the program provides the designer with a high level "language" in which to compose new designs. It then performs some of the detailed design process. The process of "compilation" is based on a formalization of quantitative inferences about hierarchically organized sets of artifacts and operating conditions. This allows the design compilation without the exhaustive enumeration of alternatives.

A Statistical Image-Based Shape Model for Visual Hull Reconstruction and 3D Structure Inference

We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

Memory Usage Inference for Object-Oriented Programs

We present a type-based approach to statically derive symbolic closed-form formulae that characterize the bounds of heap memory usages of programs written in object-oriented languages. Given a program with size and alias annotations, our inference system will compute the amount of memory required by the methods to execute successfully as well as the amount of memory released when methods return. The obtained analysis results are useful for networked devices with limited computational resources as well as embedded software.

Inference of distributional parameters from compositional samples containing nondetects

Low concentrations of elements in geochemical analyses have the peculiarity of being compositional data and, for a given level of significance, are likely to be beyond the capabilities of laboratories to distinguish between minute concentrations and complete absence, thus preventing laboratories from reporting extremely low concentrations of the analyte. Instead, what is reported is the detection limit, which is the minimum concentration that conclusively differentiates between presence and absence of the element. A spatially distributed exhaustive sample is employed in this study to generate unbiased sub-samples, which are further censored to observe the effect that different detection limits and sample sizes have on the inference of population distributions starting from geochemical analyses having specimens below detection limit (nondetects). The isometric logratio transformation is used to convert the compositional data in the simplex to samples in real space, thus allowing the practitioner to properly borrow from the large source of statistical techniques valid only in real space. The bootstrap method is used to numerically investigate the reliability of inferring several distributional parameters employing different forms of imputation for the censored data. The case study illustrates that, in general, best results are obtained when imputations are made using the distribution best fitting the readings above detection limit and exposes the problems of other more widely used practices. When the sample is spatially correlated, it is necessary to combine the bootstrap with stochastic simulation

Educaci??n formal, no formal e informal en el Espacio Europeo : nuevas exigencias para los procesos de formaci??n en educaci??n

Resumen tomado de la publicaci??n

El Madrugón en Bogotá, un mercado textil popular cuyos lazos de solidaridad reproducen órdenes comerciales y productivos de carácter informal

El presente documento explora las estrategias y características de dos unidades de trabajo vinculadas a uno de los fenómenos comerciales informales más importantes en Bogotá y que es conocido popularmente como El Madrugón, mercado en el que se venden principalmente artículos de la confección. Se trató de ilustrar en detalle y relacionalmente mediante la teoría del sociólogo Pierre Bourdieu, las diversas situaciones a nivel comercial y productivo que estructuran la permanencia en un territorio altamente competitivo y que se caracteriza por sus ventas mayoristas. Asimismo, la investigación trata de entender las lógicas comerciales de un fenómeno urbano cuyo origen está fuertemente configurado por una política pública en relación a la recuperación de un espacio público en el sector de San Victorino (Bogotá), pero también por una estructura de mercado muy particular. El objetivo principal del presente trabajo fue el de comprender cómo este territorio se construye a partir de prácticas informales que en algunos casos tienen elementos ‘Modernos’.

Educación informal. Configuración y valores de los protagonistas infantiles.

Resumen tomado de la publicación

Aprenentatge informal d'ofici i formaci?? professional a la primera fase del capitalisme : algunes reflexions sobre el cas barcelon??. 'Aprendizaje informal de oficio y formaci??n profesional en la primera fase del capitalismo : algunas reflexiones sobre el caso de Barcelona'

Estas Jornadas tuvieron lugar en Punta Prima, Menorca, en mayo de 1986 y fueron editadas por el ICE de la UIB. Resumen tomado de la propia publicaci??n. Contiene resumen en ingl??s en la p??gina 13