Statistical inference of minimum rank factor analysis
By Alexander Shapiro, J. F. Berge. 2002
121 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability, Signal Processing
View Paper: https://www.semanticscholar.org/paper/0855002fde7ff9ed69ad9fdd1a6a4851ae864c23
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- Pere J. Ferrando
- Urbano Lorenzo-Seva
- Rahul Mazumder
- Gregor Socan
- Dimitris J. Bertsimas
- Martin S. Copenhaver
- J. F. Berge
- W. D. Linden
In Statistics and Probability
- Rahul Mazumder
- Pere J. Ferrando
- Urbano Lorenzo-Seva
- Dimitris J. Bertsimas
- Gregor Socan
- Martin S. Copenhaver
- J. F. Berge
- Jack Dunn
In Signal Processing
- Urbano Lorenzo-Seva
- Pere J. Ferrando
- Dimitris J. Bertsimas
- Martin S. Copenhaver
- Rahul Mazumder
- Alwin Stegeman
Citations in the corpus
- Certifiably Optimal Low Rank Factor Analysis (2016, methodology): “Most of the methods described in Section 1.1 are widely used and their implementations are available in statistical packages psych (Revelle, 2015), nFactors (Raiche and Magis, 2011), GPArotation (Bernaards and Jennrich, 2005), and others and are publicly available from CRAN .”
- FACTOR: A computer program to fit the exploratory factor analysis model (2006, methodology): “For factor analysis, the program uses two common procedures—unweighted least squares (ULS) and exploratory maximum likelihood (EML)—plus a relatively new and unusual procedure: minimum rank factor analysis (MRFA; see, e.g., Shapiro & ten Berge, 2002; ten Berge & Kiers, 1991).”
- The greatest lower bound to the reliability of a test and the hypothesis of unidimensionality (2004, background): “Ten Berge and Kiers (1991) (also see Ten Berge (1998) and Shapiro & Ten Berge (2002) ), have proposed Minimum Rank Factor Analysis (MRFA, downloadable as mrfa2.exe from ppswmm, ppsw.”