This paper is concerned with extreme value density estimation. The generalized Pareto distribution (GPD) beyond a given threshold is combined with a nonparametric estimation approach below the threshold. This semiparametric setup is shown to generalize a few existing approaches and enables density estimation over the complete sample space. Estimation is performed via the Bayesian paradigm, which helps identify model components. Estimation of all model parameters, including the threshold and higher quantiles, and prediction for future observations is provided. Simulation studies suggest a few useful guidelines to evaluate the relevance of the proposed procedures. They also provide empirical evidence about the improvement of the proposed methodology over existing approaches. Models are then applied to environmental data sets. The paper is concluded with a few directions for future work.

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Broiler building typology associated with the local characteristics (climate, topography and surrounding vegetation) and handling systems (stocking density, curtains, equipment and nutrition) influence the inside environment. A spatial distribution analysis of these conditions may indicate stress zones in the house. The aim of this research was to apply spatial analysis of thermal, aerial and acoustic environmental conditions inside a tunnel ventilated broiler housing, with a stocking density of 18 birds m -2 . This study was carried out in Rio Claro, SP, Brazil, in a 12 m × 115 m house divided into three equal sections (East, center and West), East-West oriented, and virtually divided on 132 cells, each one measuring 3.0 m × 3.5 m. At the geometric center of each cell the following variables were monitored: dry bulb temperature, relative humidity, air velocity, noise level and light intensity. Average broiler mortality was recorded in each of the three sections. Data collection was made systematically from West to East, opposite to the air flow produced by the tunnel ventilation system, during the warmest period of the day. Measurements took place during the sixth week of production. A geostatistics software tool was used to build spatial distribution maps of the recorded variables in order to infer intermediate stress conditions. It was concluded that the stress zones were located at both ends of the house and the highest mortality index was found at the West sector where the exhaust fans were placed. Key words: broiler production, environment, geostatistics, heat stress, spatial distribution ANÁLISE ESPACIAL DE CONDIÇÕES DE ESTRESSE EM GALPÃO DE FRANGO DE CORTE USANDO VENTILAÇÃO TIPO TÚNELRESUMO: A tipologia de edificações para abrigo de frangos de corte associada a características do local (clima, topografia e vegetação dos arredores) e os sistemas de manejo (densidade de aves, cortinas, equipamentos e nutrição) influencia as condições internas. A distribuição espacial destas variáveis pode indicar zona de estresse dentro do galpão. O objetivo da pesquisa foi aplicar a análise espacial das condições do ambiente térmico, aéreo e acústico dentro de galpão de produção de frango de corte, usando sistema de ventilação tipo túnel e densidade de 18 aves m-2. O estudo foi conduzido em Rio Claro, SP, em uma edificação com 12 m × 115 m, dividida em três setores (leste, centro e oeste), orientada leste-oeste, contendo virtualmente 132 células, cada uma medindo 3,0 m × 3,5 m. No centro geométrico de cada célula as seguintes variáveis foram medidas instantaneamente: temperatura de bulbo seco, umidade relativa, velocidade do ar, nível de ruído e intensidade de luz. Os dados foram coletados sistematicamente a partir do lado oeste para o lado leste, em direção oposta ao fluxo de ar produzido pela ventilação tipo túnel, no período mais crítico do dia. As medidas foram tomadas quando as aves estavam na sexta semana de produção. A mortalidade média dos frangos foi registrada nos três setores. A ferramenta geostatísti...

This paper investigates the strategic pricing of consumer durable products which can be acquired through either purchase or reproduction (e.g., computer software). As copy piracy results in an opportunity loss, its adverse effect on profits needs to be incorporated in strategic decisions such as pricing. Using a dual diffusion model which parsimoniously describes sales and copying, and employing control theory methodology, optimal price trajectories are derived for the period of monopoly. The results indicate that (a) in absence of any protection, skimming pricing strategies are generally optimal, and (b) copy protection is warranted only when sales diffuse much faster than copying and the protection technology does not significantly raise the marginal production cost.marketing, new products, pricing

In probability theory and statistics, the generalized extreme value (GEV) distribution is a family of continuous probability distributions developed within extreme value theory, which has wide applicability in several areas including hydrology, engineering, science, ecology and finance. In this paper, we propose three extensions of the GEV distribution that incorporate an additional parameter. These extensions are more flexible than the GEV distribution, i.e., the additional parameter introduces skewness and to vary tail weight. In these three cases, the GEV distribution is a particular case. The parameter estimation of these new distributions is done under the Bayesian paradigm, considering vague priors for the parameters. Simulation studies show the efficiency of the proposed models. Applications to river quotas and rainfall show that the generalizations can produce more efficient results than is the standard case with GEV distribution.

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Many situations in practice require appropriate specification of operating characteristics under extreme conditions. Typical examples include environmental sciences where studies include extreme temperature, rainfall and river flow to name a few. In these cases, the effect of geographic and climatological inputs are likely to play a relevant role. This paper is concerned with the study of extreme data in the presence of relevant auxiliary information. The underlying model involves a mixture distribution: a generalized Pareto distribution is assumed for the exceedances beyond a high threshold and a non-parametric approach is assumed for the data below the threshold. Thus, the full likelihood including data below and above the threshold is considered in the estimation. The main novelty is the introduction of a regression structure to explain the variation of the exceedances through all tail parameters. Estimation is performed under the Bayesian paradigm and includes model choice. This allows for determination of higher quantiles under each covariate configuration and upper bounds for the data, where appropriate. Simulation results show that the models are appropriate and identifiable. The models are applied to the study of two temperature F. F. do Nascimento (B) 123 496 Environ Ecol Stat (2011) 18:495-512 datasets: maxima in the U.S.A. and minima in Brazil, and compared to other related models.