Iteratively Reweighted Least Squares

By Murray A. Jorgensen. 2006

73 citations recorded by the source corpus.

Subfields: Applied Mathematics, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fb53d90c7230232fe5efb2e12d75c34cc69522dc

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

1. Arunas P. Verbyla
2. Saralees Nadarajah
3. Tal Hassner
4. Roee Enbar
5. Eran Eidinger
6. Julian Taylor
7. Samuel Kotz

In Control and Systems Engineering

1. Arunas P. Verbyla
2. Saralees Nadarajah
3. Tal Hassner
4. Roee Enbar
5. Eran Eidinger
6. Julian Taylor
7. Samuel Kotz

In Statistics and Probability

1. Saralees Nadarajah
2. Gauss Moutinho Cordeiro
3. Samuel Kotz
4. Edwin M. M. Ortega
5. Arunas P. Verbyla
6. Tal Hassner
7. Roee Enbar
8. Eran Eidinger

Citations in the corpus

• Estimation Methods for the Multivariate t Distribution (2008, background): “To impute the missing values in an incomplete normal data set, Rubin and Schafer [48] (see also [49], and [33]) proposed an efficient method, called monotone data augmentation (MDA), and implemented it using the factorized likelihood approach.”
• Pattern Recognition and Machine Learning (2006, unknown): “For this reason, the algorithm is known as iterative reweighted least squares, or IRLS (Rubin, 1983).”
• Age and Gender Estimation of Unfiltered Faces (2014, methodology): “This process can be repeated, obtaining transformations H(2)j , H 3 j and so fourth, until convergence [66].”
• Joint modelling of location and scale parameters of the t distribution (2004, methodology): “10) are identical to evaluating the E-step of the EM algorithm for the t with known or unknown degrees of freedom (Lange et al., 1989; Liu et al., 1998; Meng and van Dyk, 1997; Pinheiro et al., 2001; Rubin, 1983).”