A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

Pharmacophore Model of Cruzain Inhibitors

Chagas disease, caused by the protozoan Trypanosoma cruzi, is one of the most serious amongst the so-called neglected diseases in Latin America, specially in Brazil. So far there has been no effective treatment for the chronic phase of this disease. Cruzain is a major cysteine protease of T cruzi and it is recognized as a valid target for Chagas disease chemotherapy. The mechanism of cruzain action is associated with the nucleophilic attack of an activated sulfur atom towards electrophilic groups. In this report, features of a putative pharmacophore model of the enzyme, developed as a virtual screening tool for the selection of potential cruzain inhibitors, are described. The final proposed model was applied to the ZINC v.7 database and afterwards experimentally validated by an enzymatic inhibition assay. One of the compounds selected by the model showed cruzain inhibition in the low micromolar range.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Legal LEGO: Model based computer assisted teaching in evidence courses

This paper describes the development of a new approach to the use of ICT for the teaching of courses in the interpretation and evaluation of evidence. It is based on ideas developed for the teaching of science to school children, in particular the importance of models and qualitative reasoning skills. In the first part, we make an analysis of the basis of current research into “evidence scholarship” and the demands such a system would have to meet. In the second part, we introduce the details of such a system that we developed initially to assist police in the interpretation of evidence.

Mapping Attribution Metadata to the Open Provenance Model

A description of a data item's provenance can be provided in dierent forms, and which form is best depends on the intended use of that description. Because of this, dierent communities have made quite distinct underlying assumptions in their models for electronically representing provenance. Approaches deriving from the library and archiving communities emphasise agreed vocabulary by which resources can be described and, in particular, assert their attribution (who created the resource, who modied it, where it was stored etc.) The primary purpose here is to provide intuitive metadata by which users can search for and index resources. In comparison, models for representing the results of scientific workflows have been developed with the assumption that each event or piece of intermediary data in a process' execution can and should be documented, to give a full account of the experiment undertaken. These occurrences are connected together by stating where one derived from, triggered, or otherwise caused another, and so form a causal graph. Mapping between the two approaches would be benecial in integrating systems and exploiting the strengths of each. In this paper, we specify such a mapping between Dublin Core and the Open Provenance Model. We further explain the technical issues to overcome and the rationale behind the approach, to allow the same method to apply in mapping similar schemes.

A Resource Centric Approach For Advancing Collaboration Through Hydrologic Data And Model Sharing

HydroShare is an online, collaborative system being developed for open sharing of hydrologic data and models. The goal of HydroShare is to enable scientists to easily discover and access hydrologic data and models, retrieve them to their desktop or perform analyses in a distributed computing environment that may include grid, cloud or high performance computing model instances as necessary. Scientists may also publish outcomes (data, results or models) into HydroShare, using the system as a collaboration platform for sharing data, models and analyses. HydroShare is expanding the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated, creating new capability to share models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. One of the fundamental concepts in HydroShare is that of a Resource. All content is represented using a Resource Data Model that separates system and science metadata and has elements common to all resources as well as elements specific to the types of resources HydroShare will support. These will include different data types used in the hydrology community and models and workflows that require metadata on execution functionality. The HydroShare web interface and social media functions are being developed using the Drupal content management system. A geospatial visualization and analysis component enables searching, visualizing, and analyzing geographic datasets. The integrated Rule-Oriented Data System (iRODS) is being used to manage federated data content and perform rule-based background actions on data and model resources, including parsing to generate metadata catalog information and the execution of models and workflows. This presentation will introduce the HydroShare functionality developed to date, describe key elements of the Resource Data Model and outline the roadmap for future development.

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.

Temperature Dynamics Investigation At Small And Shallow Lakes Using Hydrodynamic Model

A three-dimensional time-dependent hydrodynamic and heat transport model of Lake Binaba, a shallow and small dam reservoir in Ghana, emphasizing the simulation of dynamics and thermal structure has been developed. Most numerical studies of temperature dynamics in reservoirs are based on one- or two-dimensional models. These models are not applicable for reservoirs characterized with complex flow pattern and unsteady heat exchange between the atmosphere and water surface. Continuity, momentum and temperature transport equations have been solved. Proper assignment of boundary conditions, especially surface heat fluxes, has been found crucial in simulating the lake’s hydrothermal dynamics. This model is based on the Reynolds Average Navier-Stokes equations, using a Boussinesq approach, with a standard k − ε turbulence closure to solve the flow field. The thermal model includes a heat source term, which takes into account the short wave radiation and also heat convection at the free surface, which is function of air temperatures, wind velocity and stability conditions of atmospheric boundary layer over the water surface. The governing equations of the model have been solved by OpenFOAM; an open source, freely available CFD toolbox. As its core, OpenFOAM has a set of efficient C++ modules that are used to build solvers. It uses collocated, polyhedral numerics that can be applied on unstructured meshes and can be easily extended to run in parallel. A new solver has been developed to solve the hydrothermal model of lake. The simulated temperature was compared against a 15 days field data set. Simulated and measured temperature profiles in the probe locations show reasonable agreement. The model might be able to compute total heat storage of water bodies to estimate evaporation from water surface.

On a uniform turnpike of the third kind in the Robinson-Solow-Srinivasan model

On using McKenzie’s taxonomy of optimal accumulation in the longrun, we report a “uniform turnpike” theorem of the third kind in a model original to Robinson, Solow and Srinivasan (RSS), and further studied by Stiglitz. Our results are presented in the undiscounted, discrete-time setting emphasized in the recent work of Khan-Mitra, and they rely on the importance of strictly concave felicity functions, or alternatively, on the value of a “marginal rate of transformation”, ξσ, from one period to the next not being unity. Our results, despite their specificity, contribute to the methodology of intertemporal optimization theory, as developed in economics by Ramsey, von Neumann and their followers.

A model to estimate the US term structure of interest rates

The US term structure of interest rates plays a central role in fixed-income analysis. For example, estimating accurately the US term structure is a crucial step for those interested in analyzing Brazilian Brady bonds such as IDUs, DCBs, FLIRBs, EIs, etc. In this work we present a statistical model to estimate the US term structure of interest rates. We address in this report all major issues which drove us in the process of implementing the model developed, concentrating on important practical issues such as computational efficiency, robustness of the final implementation, the statistical properties of the final model, etc. Numerical examples are provided in order to illustrate the use of the model on a daily basis.

The Aiyagari model with liquidity shoch

Neste trabalho é desenvolvida uma versão do modelo de Aiyagari (1994) com choque de liquidez. Este modelo tem Huggett (1993) e Aiyagari (1994) como casos particulares, mas esta generalização permite dois ativos distintos na economia, um líquido e outro ilíquido. Usar dois ativos diferentes implica em dois retornos afetando o "market clearing", logo, a estratégia computacional usada por Aiyagari e Hugget não funciona. Consequentemente, a triangulação de Scarf substitui o algoritmo. Este experimento computacional mostra que o retorno em equilíbrio do ativo líquido é menor do que o retorno do ilíquido. Além disso, pessoas pobres carregam relativamente mais o ativo líquido, e essa desigualdade não aparece no modelo de Aiyagari.

A time-varying markov-switching model for economic growth

This paper investigates economic growth’s pattern of variation across and within countries using a Time-Varying Transition Matrix Markov-Switching Approach. The model developed follows the approach of Pritchett (2003) and explains the dynamics of growth based on a collection of different states, each of which has a sub-model and a growth pattern, by which countries oscillate over time. The transition matrix among the different states varies over time, depending on the conditioning variables of each country, with a linear dynamic for each state. We develop a generalization of the Diebold’s EM Algorithm and estimate an example model in a panel with a transition matrix conditioned on the quality of the institutions and the level of investment. We found three states of growth: stable growth, miraculous growth, and stagnation. The results show that the quality of the institutions is an important determinant of long-term growth, whereas the level of investment has varying roles in that it contributes positively in countries with high-quality institutions but is of little relevance in countries with medium- or poor-quality institutions.

From commitment to non-commitment: allowing type dynamic in Laffont and Tirole's regulation model

This paper investigates the introduction of type dynamic in the La ont and Tirole's regulation model. The regulator and the rm are engaged in a two period relationship governed by short-term contracts, where, the regulator observes cost but cannot distinguish how much of the cost is due to e ort on cost reduction or e ciency of rm's technology, named type. There is asymmetric information about the rm's type. Our model is developed in a framework in which the regulator learns with rm's choice in the rst period and uses that information to design the best second period incentive scheme. The regulator is aware of the possibility of changes in types and takes that into account. We show how type dynamic builds a bridge between com- mitment and non-commitment situations. In particular, the possibility of changing types mitigates the \ratchet e ect". We show that for small degree of type dynamic the equilibrium shows separation and the welfare achived is close to his upper bound (given by the commitment allocation).

In search of exchange rate predictability : a study about accuracy, consistency, and granger causality of forecasts generated by a Taylor Rule Model

Este estudo investiga o poder preditivo fora da amostra, um mês à frente, de um modelo baseado na regra de Taylor para previsão de taxas de câmbio. Revisamos trabalhos relevantes que concluem que modelos macroeconômicos podem explicar a taxa de câmbio de curto prazo. Também apresentamos estudos que são céticos em relação à capacidade de variáveis macroeconômicas preverem as variações cambiais. Para contribuir com o tema, este trabalho apresenta sua própria evidência através da implementação do modelo que demonstrou o melhor resultado preditivo descrito por Molodtsova e Papell (2009), o “symmetric Taylor rule model with heterogeneous coefficients, smoothing, and a constant”. Para isso, utilizamos uma amostra de 14 moedas em relação ao dólar norte-americano que permitiu a geração de previsões mensais fora da amostra de janeiro de 2000 até março de 2014. Assim como o critério adotado por Galimberti e Moura (2012), focamos em países que adotaram o regime de câmbio flutuante e metas de inflação, porém escolhemos moedas de países desenvolvidos e em desenvolvimento. Os resultados da nossa pesquisa corroboram o estudo de Rogoff e Stavrakeva (2008), ao constatar que a conclusão da previsibilidade da taxa de câmbio depende do teste estatístico adotado, sendo necessária a adoção de testes robustos e rigorosos para adequada avaliação do modelo. Após constatar não ser possível afirmar que o modelo implementado provém previsões mais precisas do que as de um passeio aleatório, avaliamos se, pelo menos, o modelo é capaz de gerar previsões “racionais”, ou “consistentes”. Para isso, usamos o arcabouço teórico e instrumental definido e implementado por Cheung e Chinn (1998) e concluímos que as previsões oriundas do modelo de regra de Taylor são “inconsistentes”. Finalmente, realizamos testes de causalidade de Granger com o intuito de verificar se os valores defasados dos retornos previstos pelo modelo estrutural explicam os valores contemporâneos observados. Apuramos que o modelo fundamental é incapaz de antecipar os retornos realizados.

Does mixed frequency vector error correction model add relevant information to exchange misalignment calculus? Evidence for United States

Real exchange rate is an important macroeconomic price in the economy and a ects economic activity, interest rates, domestic prices, trade and investiments ows among other variables. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that it is possible to calculate the misalignment from a mixed ointegrated vector error correction framework. An empirical exercise using United States' real exchange rate data is performed. The results suggest that the model with mixed frequency data is preferred to the models with same frequency variables