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Recent Developments in Modeling and Applications in Statistics / edited by Paulo Eduardo Oliveira, Maria da Graça Temido, Carla Henriques, Maurizio Vichi.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Studies in Theoretical and Applied StatisticsEditor: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Descripción: xxI, 269 páginas 56 ilustraciones, 17 ilustraciones en color. recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783642324192
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA276-280
Recursos en línea:
Contenidos:
Sampling and Modeling -- Estimation -- Extremes -- Testing Statistical Hypothesis -- Models with Stochastic Differential Equations -- Stochastic Processes.  .
Resumen: Statistics has been a main tool in almost every field of activity and an essential part of applied scientific work, supporting conclusions and offering insights into new uses for established methodologies, thus making it a valuable resource in looking for faceless facts. Model construction describing populations or phenomena subject to randomness use a wide range of methods. Data collection provides the basis for modeling and assumption verification. Modeling must be conducted using suitable techniques that give researchers the means to search for hidden facts or behaviors. This may be addressed by fitting pre-defined shapes and distributions to the data or by allowing the data to reveal its intrinsic properties by using nonparametric methods. This volume contains a selection of contributions presented at the XVIII Annual Congress of the Portuguese Statistical Society.
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Sampling and Modeling -- Estimation -- Extremes -- Testing Statistical Hypothesis -- Models with Stochastic Differential Equations -- Stochastic Processes.  .

Statistics has been a main tool in almost every field of activity and an essential part of applied scientific work, supporting conclusions and offering insights into new uses for established methodologies, thus making it a valuable resource in looking for faceless facts. Model construction describing populations or phenomena subject to randomness use a wide range of methods. Data collection provides the basis for modeling and assumption verification. Modeling must be conducted using suitable techniques that give researchers the means to search for hidden facts or behaviors. This may be addressed by fitting pre-defined shapes and distributions to the data or by allowing the data to reveal its intrinsic properties by using nonparametric methods. This volume contains a selection of contributions presented at the XVIII Annual Congress of the Portuguese Statistical Society.

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