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Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series

Estela Bee Dagum Pierre A. Cholette

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Palabras clave – provistas por la editorial

Econometrics; Statistics for Business/Economics/Mathematical Finance/Insurance; Statistical Theory and Methods

Disponibilidad
Institución detectada Año de publicación Navegá Descargá Solicitá
No detectada 2006 SpringerLink

Información

Tipo de recurso:

libros

ISBN impreso

978-0-387-31102-9

ISBN electrónico

978-0-387-35439-2

Editor responsable

Springer Nature

País de edición

Reino Unido

Fecha de publicación

Información sobre derechos de publicación

© Springer Science+Business Media, LLC 2006

Cobertura temática

Tabla de contenidos

Reconciliation and Balancing Systems of Time Series

Estela Bee Dagum; Pierre A. Cholette

In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.

Pp. 263-284

Reconciling One-Way Classified Systems of Time Series

Estela Bee Dagum; Pierre A. Cholette

In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.

Pp. 285-307

Reconciling the Marginal Totals of Two-Way Classified Systems of Series

Estela Bee Dagum; Pierre A. Cholette

In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.

Pp. 309-336

Reconciling Two-Way Classifed Systems of Series

Estela Bee Dagum; Pierre A. Cholette

In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.

Pp. 337-362