Bibliografías temáticas / Covariance matrice / Libros
Siga este enlace para ver otros tipos de publicaciones sobre el tema: Covariance matrice.

Libros sobre el tema "Covariance matrice"

Autor: Grafiati
Publicado: 11 de marzo de 2023

Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros

Elija tipo de fuente:

Consulte los 25 mejores mejores libros para su investigación sobre el tema "Covariance matrice".

Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.

También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.

Explore libros sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.

1

Tsukuma, Hisayuki y Tatsuya Kubokawa. Shrinkage Estimation for Mean and Covariance Matrices. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1596-5.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
2

Jong, Robert M. de. Consistency of kernel estimators of heteroscedastic and autocorrelated covariance matrices. Cardiff: Cardiff Business School, 1996.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
3

Srivastava, M. S. Classification with a preassigned error rate when two covariance matrices are equal. Toronto: University of Toronto, Dept. of Statistics, 1998.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
4

Woodruff, David. A note on a relationship between covariance matrices and consistently estimated variance components. Iowa City, Iowa: American College Testing Program, 1995.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
5

U.S. Nuclear Regulatory Commission. Division of Systems Analysis and Regulatory Effectiveness. y Oak Ridge National Laboratory, eds. PUFF-III: A code for processing ENDF uncertainty data into multigroup covariance matrices. Washington, DC: U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, 2000.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
6

U.S. Nuclear Regulatory Commission. Division of Systems Analysis and Regulatory Effectiveness. y Oak Ridge National Laboratory, eds. PUFF-III: A code for processing ENDF uncertainty data into multigroup covariance matrices. Washington, DC: U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, 2000.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
7

Kubokawa, T. Robust improvements in estimation of mean and covariance matrices in elliptically contoured distribution. Toronto: University of Toronto, Dept. of Statistics, 1997.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
8

Pynnönen, Seppo. Testing for additional information in variables in multivariate normal classification with unequal covariance matrices. Vaasa: Universitas Wasaensis, 1988.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
9

Bose, Arup y Monika Bhattacharjee. Large Covariance and Autocovariance Matrices. Taylor & Francis Group, 2018.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
10

Bose, Arup. Large Covariance and Autocovariance Matrices. Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9780203730652.

Texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
11

Bose, Arup y Monika Bhattacharjee. Large Covariance and Autocovariance Matrices. Taylor & Francis Group, 2018.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
12

Bose, Arup y Monika Bhattacharjee. Large Covariance and Autocovariance Matrices. Taylor & Francis Group, 2020.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
13

Large Covariance and Autocovariance Matrices. Taylor & Francis Group, 2018.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
14

Bose, Arup y Monika Bhattacharjee. Large Covariance and Autocovariance Matrices. Taylor & Francis Group, 2018.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
15

Bose, Arup y Monika Bhattacharjee. Large Covariance and Autocovariance Matrices. Taylor & Francis Group, 2018.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
16

Tsukuma, Hisayuki y Tatsuya Kubokawa. Shrinkage Estimation for Mean and Covariance Matrices. Springer, 2020.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
17

Tsukuma, Hisayuki y Tatsuya Kubokawa. Shrinkage Estimation for Mean and Covariance Matrices. Springer, 2020.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
18

Bai, Zhidong, Jianfeng Yao y Shurong Zheng. Large Sample Covariance Matrices and High-Dimensional Data Analysis. Cambridge University Press, 2015.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
19

Large Sample Covariance Matrices and High-Dimensional Data Analysis. Cambridge University Press, 2015.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
20

Zinn-Justin, Paul y Jean-Bernard Zuber. Multivariate statistics. Editado por Gernot Akemann, Jinho Baik y Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.28.

Texto completo
Resumen
This article considers some classical and more modern results obtained in random matrix theory (RMT) for applications in statistics. In the classic paradigm of parametric statistics, data are generated randomly according to a probability distribution indexed by parameters. From this data, which is by nature random, the properties of the deterministic (and unknown) parameters may be inferred. The ability to infer properties of the unknown Σ (the population covariance matrix) will depend on the quality of the estimator. The article first provides an overview of two spectral statistical techniques, principal components analysis (PCA) and canonical correlation analysis (CCA), before discussing the Wishart distribution and normal theory. It then describes extreme eigenvalues and Tracy–Widom laws, taking into account the results obtained in the asymptotic setting of ‘large p, large n’. It also analyses the results for the limiting spectra of sample covariance matrices..
Los estilos APA, Harvard, Vancouver, ISO, etc.
21

PUFF-III: A code for processing ENDF uncertainty data into multigroup covariance matrices. Washington, DC: U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, 2000.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
22

A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more. FE Press, LLC, 2014.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
23

Baulieu, Laurent, John Iliopoulos y Roland Sénéor. Relativistic Wave Equations. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198788393.003.0006.

Texto completo
Resumen
Relativistically covariant wave equations for scalar, spinor, and vector fields. Plane wave solutions and Green’s functions. The Klein–Gordon equation. The Dirac equation and the Clifford algebra of γ‎ matrices. Symmetries and conserved currents. Hamiltonian and Lagrangian formulations. Wave equations for spin-1 fields.
Los estilos APA, Harvard, Vancouver, ISO, etc.
24

Chirembo, Anderson Mayotcha. Direct versus indirect methods for the estimation of variance-covariance matrices and regression parameters when data are skewed and incomplete. 1995.

Buscar texto completo
Los estilos APA, Harvard, Vancouver, ISO, etc.
25

Back, Kerry E. Factor Models. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0006.

Texto completo
Resumen
The CAPM and factor models in general are explained. Factors can be replaced by the returns or excess returns that are maximally correlated (the projections of the factors). A factor model is equivalent to an affine representation of an SDF and to spanning a return on the mean‐variance frontier. The use of alphas for performance evaluation is explained. Statistical factor models are defined as models in which factors explain the covariance matrix of returns. A proof is given of the Arbitrage Pricing Theory, which states that statistical factors are approximate pricing factors. The CAPM and the Fama‐French‐Carhart model are evaluated relative to portfolios based on sorts on size, book‐to‐market, and momentum.
Los estilos APA, Harvard, Vancouver, ISO, etc.
También puede estar interesado en las bibliografías sobre el tema "Covariance matrice" para otros tipos de fuentes:
Artículos de revistas Tesis
Ofrecemos descuentos en todos los planes premium para autores cuyas obras están incluidas en selecciones literarias temáticas. ¡Contáctenos para obtener un código promocional único!

Pasar a la bibliografía