In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). Typically… (More)

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2009

2009

- Felipe P. do Carmo, Vania V. Estrela, Joaquim Teixeira de Assis
- 2009 IEEE International Workshop on Multimedia…
- 2009

In this paper, two simple principal component regression methods for estimating the optical flow between frames of video… (More)

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2007

Highly Cited

2007

The pls package implements principal component regression (PCR) and partial least squares regression (PLSR) in R (R Development… (More)

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2007

2007

- Christiaan Heij, Patrick J. F. Groenen, Dick van Dijk
- Computational Statistics & Data Analysis
- 2007

Forecasting with many predictors is of interest, for instance, in macroeconomics and finance. This paper compares two methods for… (More)

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2003

2003

- Renzhong Liu, J. Kuang, Q. Gong, X. L. Hou
- Computer Methods and Programs in Biomedicine
- 2003

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and… (More)

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2003

Highly Cited

2003

- Mike West
- 2003

I discuss Bayesian factor regression models and prediction with very many explanatory variables. Such problems arise in many… (More)

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2001

2001

- Peter Filzmoser
- 2001

In this note we introduce a method for robust principal component regression. Robust principal components are computed from the… (More)

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2001

Highly Cited

2001

- Roman Rosipal, Leonard J. Trejo
- Journal of Machine Learning Research
- 2001

A family of regularized least squares regression models in a Reproducing Kernel Hilbert Space is extended by the kernel partial… (More)

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1999

1999

- Nikos A. Vlassis, Ben J. A. Kröse
- IROS
- 1999

A key issue in mobile robot applications involves building a map of the environment to be used by the robot for localization and… (More)

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1999

Highly Cited

1999

- Christopher J. Merz, Michael J. Pazzani
- Machine Learning
- 1999

The goal of combining the predictions of multiple learned models is to form an improved estimator. A combining strategy must be… (More)

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1997

1997

- Rik Wehrens
- 1997

Bootstrap methods can be used as an alternative for cross-validation in regression procedures such as principal component… (More)

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