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  • A.C. Davison

    Publicado por Cambridge University Press, Cambridge, 1997

    ISBN 10: 0521574714 ISBN 13: 9780521574716

    Idioma: Inglés

    Librería: CitiRetail, Stevenage, Reino Unido

    Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

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    Original o primera edición

    EUR 34,60 gastos de envío desde Reino Unido a España

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    Cantidad disponible: 1 disponibles

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    Paperback. Condición: new. Paperback. Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website. This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • A.C. Davison

    Publicado por Cambridge University Press, Cambridge, 1997

    ISBN 10: 0521574714 ISBN 13: 9780521574716

    Idioma: Inglés

    Librería: AussieBookSeller, Truganina, VIC, Australia

    Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

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    Original o primera edición

    EUR 31,43 gastos de envío desde Australia a España

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    Cantidad disponible: 1 disponibles

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    Paperback. Condición: new. Paperback. Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website. This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • A.C. Davison

    Publicado por Cambridge University Press, Cambridge, 1997

    ISBN 10: 0521574714 ISBN 13: 9780521574716

    Idioma: Inglés

    Librería: Grand Eagle Retail, Mason, OH, Estados Unidos de America

    Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

    Contactar al vendedor

    Original o primera edición

    EUR 63,70 gastos de envío desde Estados Unidos de America a España

    Destinos, gastos y plazos de envío

    Cantidad disponible: 1 disponibles

    Añadir al carrito

    Paperback. Condición: new. Paperback. Bootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website. This book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: Shipping may be from multiple locations in the US or from the UK, depending on stock availability.