Matrix Analysis for Statistics

By James R. Schott. 2005

475 citations recorded by the source corpus.

Subfields: Applied Mathematics, Computational Theory and Mathematics, Modeling and Simulation

View Paper: https://www.semanticscholar.org/paper/ae5a1eee79212aa6fbef25d39d75d7a3f8c97803

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Mathematics

In Computational Theory and Mathematics

In Modeling and Simulation

Citations in the corpus

Contemporary Bayesian Econometrics and Statistics (2005, background): “Necessary and sufficient conditions for a nonsymmetric matrix to be diagonable can be found in many linear algebra texts, for example, Schott (1997), Section 4.”
Multiple-Group Analysis for Structural Equation Modeling With Dependent Samples (2015, background): “Let Dp be the duplication matrix such that vec ( j ) = Dpvech ( j) (e.g., Schott, 2005, p. 313) and Wj = diag [ −1j , 2 −1D′p ( −1j ⊗ −1j ) Dp ] , which is the weight matrix or the inverse of the information matrix associated with the saturated model for the jth group.”
Multivariate Theory for Analyzing High Dimensional Data (2007, unknown): “see Rao (1973, p. 27), Rao and Mitra (1971, p. 208), Schott (1997) , or Siotani et al. (1985, p. 595).”
Greenhouse–Geisser Adjustment and the ANOVA-Type Statistic: Cousins or Twins? (2009, background): “The direct sum of matrices Ai, i = 1, . . . , a, is the block diagonal matrix a⊕ i=1 Ai = ⎛ ⎜⎝ A1 (0) (0) (0) . . . (0) (0) (0) Aa ⎞ ⎟⎠ , and the vec operator stacks the n columns of an m × n matrix on top of each other, resulting in an mn × 1 vector (see, e.g., Schott 2005, chap.”
ASYMPTOTIC DISTRIBUTIONS FOR TWO ESTIMATORS OF THE SINGLE-INDEX MODEL (2006, methodology): “Therefore by the mat ix inversion formula in blocks (Schott, 1997), we have”
Weed Abundance, Distribution, Diversity, and Community Analyses (2015, unknown): “Summary details about matrix algebra are presented by Digby and Kempton (1987), and Khattree and Naik (2000), whereas further details with statistical viewpoints can be found in books by Harville (1997), Rao and Rao (1998), and Schott (2005).”
Alignment-free sequence comparison-a review (2003, background): “For a comprehensive introductory study of linear algebra and vector spaces see Strang (1988) and for an introduction to matrix analysis Schott (1997) is recommended.”
Inference in Group Factor Models With an Application to Mixed‐Frequency Data (2019, background): “10.21 in Schott (2005) which provide the covariance between two quadratic forms of Gaussian vectors.”