Copt samuel (9 resultados)
Robust Methods in Biostatistics
Heritier, Stephane; Cantoni, Eva; Copt, Samuel; Victoria-feser, Maria-pia
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 105,75
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Robust Methods in Biostatistics
Heritier, Stephane; Cantoni, Eva; Copt, Samuel; Victoria-feser, Maria-pia
- Tapa dura
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 107,88
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Condición: As New. Unread book in perfect condition.
Robust Methods in Biostatistics
Heritier, Stephane; Cantoni, Eva; Copt, Samuel; Victoria-Feser, Maria-Pia
- Tapa dura
Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 101,51
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Condición: New. In.
Robust Methods in Biostatistics
Heritier, Stephane; Cantoni, Eva; Copt, Samuel; Victoria-feser, Maria-pia
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 99,11
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Condición: New.
Robust Methods in Biostatistics
Heritier, Stephane; Cantoni, Eva; Copt, Samuel; Victoria-feser, Maria-pia
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 109,43
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Condición: As New. Unread book in perfect condition.
Robust Methods in Biostatistics
Stephane Heritier, Eva Cantoni, Samuel Copt, Maria-Pia Victoria-Feser
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 129,68
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Hardback. Condición: New. Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated m…odels as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regressionGeneralized linear modelsLinear mixed modelsMarginal longitudinal data modelsCox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 129,42
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Condición: New. pp. 294 Illus.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 142,74
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Condición: New. pp. 294 Index 1st Edition.
Robust Methods in Biostatistics
Stephane Heritier, Eva Cantoni, Samuel Copt, Maria-Pia Victoria-Feser
- Tapa dura
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 121,60
Envío por EUR 75,87Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Hardback. Condición: New. Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated m…odels as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regressionGeneralized linear modelsLinear mixed modelsMarginal longitudinal data modelsCox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.
