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Publicado por Wiley-Blackwell 2020-10-14, 2020
ISBN 10: 1119392373 ISBN 13: 9781119392378
Idioma: Inglés
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Añadir al carritoCondición: New. 2020. 2nd Edition. Hardcover. . . . . .
Publicado por John Wiley and Sons Ltd, 2020
ISBN 10: 1119392373 ISBN 13: 9781119392378
Idioma: Inglés
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Publicado por John Wiley & Sons Inc, New York, 2020
ISBN 10: 1119392373 ISBN 13: 9781119392378
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Añadir al carritoHardcover. Condición: new. Hardcover. Handbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include: Regularization methodsSmoothing methodsTree-based methods In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians. Revised edition of: Handbook of regression analysis. 2013. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Añadir al carritoCondición: New. 2020. 2nd Edition. Hardcover. . . . . . Books ship from the US and Ireland.
Publicado por John Wiley & Sons Inc, New York, 2020
ISBN 10: 1119392373 ISBN 13: 9781119392378
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Añadir al carritoHardcover. Condición: new. Hardcover. Handbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include: Regularization methodsSmoothing methodsTree-based methods In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians. Revised edition of: Handbook of regression analysis. 2013. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Publicado por John Wiley & Sons Inc, New York, 2020
ISBN 10: 1119392373 ISBN 13: 9781119392378
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 209,91
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Añadir al carritoHardcover. Condición: new. Hardcover. Handbook and reference guide for students and practitioners of statistical regression-based analyses in R Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors' thorough treatment of "classical" regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data. The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include: Regularization methodsSmoothing methodsTree-based methods In the new edition of the Handbook, the data analyst's toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website. Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians. Revised edition of: Handbook of regression analysis. 2013. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.