Considering Horn's parallel analysis from a random matrix theory point of view
DOI10.1007/s11336-016-9515-zzbMath1360.62531OpenAlexW2531307915WikidataQ39293163 ScholiaQ39293163MaRDI QIDQ525237
Marieke E. Timmerman, Edoardo Saccenti
Publication date: 28 April 2017
Published in: Psychometrika (Search for Journal in Brave)
Full work available at URL: https://pure.rug.nl/ws/files/40284974/SaccentiTimmerman_Psychometrika_2017_accversion.pdf
principal component analysiscovariance matrixcommon factor analysisnumber of common factorsnumber of principal components
Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to psychology (62P15)
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Tracy-Widom law for the extreme eigenvalues of sample correlation matrices
- Edge universality of correlation matrices
- How many principal components? Stopping rules for determining the number of non-trivial axes revisited
- A boundary value problem associated with the second Painleve transcendent and the Korteweg-de Vries equation
- Level-spacing distributions and the Airy kernel
- A note on universality of the distribution of the largest eigenvalues in certain sample covariance matrices
- Bootstrap confidence intervals. With comments and a rejoinder by the authors
- On the distribution of the largest eigenvalue in principal components analysis
- Principal component analysis.
- On orthogonal and symplectic matrix ensembles
- Explaining the single factor bias of arbitrage pricing models in finite samples
- A rationale and test for the number of factors in factor analysis
- Distribution of the largest eigenvalue for real Wishart and Gaussian random matrices and a simple approximation for the Tracy-Widom distribution
- Tracy-Widom limit for the largest eigenvalue of a large class of complex sample covariance matrices
- Random matrix theory in statistics: a review
- Eigenvalues of large sample covariance matrices of spiked population models
- Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices
- Some necessary conditions for common-factor analysis
- On the numerical evaluation of Fredholm determinants
- The Distributions of Random Matrix Theory and their Applications
- Missing Data, Imputation, and the Bootstrap
- On the Numerical Evaluation of Distributions in Random Matrix Theory: A Review
This page was built for publication: Considering Horn's parallel analysis from a random matrix theory point of view
