Keywords
Computer science
Affiliated Institutions
Related Publications
On the misuse of residuals in ecology: regression of residuals vs. multiple regression
1 Residuals from linear regressions are used frequently in statistical analysis, often for the purpose of controlling for unwanted effects in multivariable datasets. This paper ...
Glove: Global Vectors for Word Representation
Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the o...
Asymptotic Theory for ARCH Models: Estimation and Testing
In the context of a linear dynamic model with moving average errors, we consider a heteroscedastic model which represents an extension of the ARCH model introduced by Engle [4]....
Finite-Dimensional Approximation of Gaussian Processes
Gaussian process (GP) prediction suffers from O(n3) scaling with the data set size n. By using a finite-dimensional basis to approximate the GP predictor, the computational comp...
Efficient implementation of gaussian processes
Neural networks and Bayesian inference provide a useful framework within which to solve regression problems. However their parameterization means that the Bayesian analysis of n...
Publication Info
- Year
- 2001
- Type
- book
- Citations
- 9098
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
9098
OpenAlex
Cite This
Frank E. Harrell
(2001).
Regression Modeling Strategies.
Springer series in statistics
.
https://doi.org/10.1007/978-1-4757-3462-1
Identifiers
- DOI
- 10.1007/978-1-4757-3462-1