J
Jeffrey S. Simonoff
Researcher at New York University
Publications - 160
Citations - 8403
Jeffrey S. Simonoff is an academic researcher from New York University. The author has contributed to research in topics: Estimator & Regression analysis. The author has an hindex of 36, co-authored 157 publications receiving 7827 citations. Previous affiliations of Jeffrey S. Simonoff include University of Southern California & University of Wisconsin-Madison.
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Smoothing Methods in Statistics
TL;DR: In this article, a nonparametric/parametric Compromise is used to improve the kernel density estimator, and the effect of simple Density Estimators is discussed.
Journal ArticleDOI
Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion
TL;DR: In this paper, an improved version of a criterion based on the Akaike information criterion (AIC), termed AICc, is derived and examined as a way to choose the smoothing parameter.
Book ChapterDOI
Multivariate Density Estimation
TL;DR: Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariateData and the comparative lack of parametric models to represent it.
Journal ArticleDOI
Procedures for the Identification of Multiple Outliers in Linear Models
Ali S. Hadi,Jeffrey S. Simonoff +1 more
TL;DR: In this paper, the authors introduce two test procedures for the detection of multiple outliers that appear to be less sensitive to the observations they are supposed to identify, and compare them with various existing methods.
Posted Content
Tree Induction Vs. Logistic Regression: a Learning-Curve Analysis
TL;DR: A large-scale experimental comparison of logistic regression and tree induction is presented, assessing classification accuracy and the quality of rankings based on class-membership probabilities, and a learning-curve analysis is used to examine the relationship of these measures to the size of the training set.