Applied Linear Statistical Models

By M. Kutner. 1975

How researchers see this paper

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

1. L. Garamszegi
2. Eric B. Laber
3. Daniel J. Lizotte
4. Shinichi Nakagawa
5. Nicolas Papernot
6. Nicholas Carlini
7. Mike W. Peng
8. Mike W.-L. Cheung

Citations in the corpus

• Adversarial Perturbations Against Deep Neural Networks for Malware Classification (2016, background): “Neural Networks are machine learning models capable of solving a variety of tasks ranging from classification [12, 4] to regression [15] and dimensionality reduction [11].”
• Informing sequential clinical decision-making through reinforcement learning: an empirical study (2010, methodology): “With the exception of the log(n) term, this test statistic resembles an F statistic in regression (Neter et al. 1996).”
• The Impact of Family Ownership, Management and Governance on Innovation (2015, unknown): “61, well below the value of 10 that is commonly used as an indicator of multi-collinearity (Neter et al., 1985).”