A New Dimension Reduction Approach for Data-Rich Marketing Environments: Sliced Inverse Regression

By Prasad A. Naik, M. Hagerty, Chih-Ling Tsai. 2000

53 citations recorded by the source corpus.

Subfields: Food Science, Marketing, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/c9972d289b2f692c9ce4ac5869261723d8fbb22f

How researchers see this paper

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

In Food Science

1. Prasad A. Naik
2. Chih-Ling Tsai
3. Roland T. Rust
4. Katherine N. Lemon
5. V. Zeithaml
6. R. Dennis Cook
7. Kalyan Raman
8. Liliana Forzani

In Marketing

1. Katherine N. Lemon
2. Roland T. Rust
3. V. Zeithaml
4. Prasad A. Naik
5. Xueming Luo
6. Peter C. Verhoef
7. Vinay Kumar
8. Christian Homburg

In Statistics and Probability

1. Chih-Ling Tsai
2. Prasad A. Naik
3. R. Dennis Cook
4. Y. Aragon
5. Kerby Shedden
6. Thomas Agnan
7. Roland T. Rust
8. Katherine N. Lemon

Citations in the corpus

• Single‐index model selections (2001, background): “Hence, single-index models offer the desired flexibility for estimating hedonic price functions.”
• Dimension Reduction for Multivariate Response Data (2003, methodology): “A comparison of SIR and PCA regression was given by Naik, Hagerty, and Tsai (2000).”
• Return on Marketing: Using Customer Equity to Focus Marketing Strategy (2004, methodology): “Principal components regression is a two-stage procedure that is widely known and applied in statistics, econometrics, and marketing (e.g., Freund and Wilson 1998; Hocking 1996; Naik, Hagerty, and Tsai 2000; Press 1982).”