Nancy E. Heckman

Q: What Schools Are Affiliated With Nancy E. Heckman

Nancy E. Heckman is affiliated with the following schools: University of British Columbia, University of Michigan

Nancy E. Heckman's AcademicInfluence.com Rankings

Nancy E. Heckman

Mathematics

#7172

World Rank

#9801

Historical Rank

Statistics

#922

World Rank

#1016

Historical Rank

mathematics Degrees

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Mathematics

Why Is Nancy E. Heckman Influential?

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According to Wikipedia, Nancy E. Heckman is a Canadian statistician, interested in nonparametric regression, smoothing, functional data analysis, and applications of statistics in evolutionary biology. From 2008 to 2018, she served as head of the statistics department at the University of British Columbia.

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Nancy E. Heckman's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Local polynomial kernel regression for generalized linear models and quasi-likelihood functions (1995) (401)
Spline Smoothing in a Partly Linear Model (1986) (391)
A quantitative genetic model for growth, shape, reaction norms, and other infinite-dimensional characters (1989) (379)
Sexual selection when the female directly benefits (1993) (270)
Penalized regression with model‐based penalties (2000) (125)
Testing for monotonicity of a regression mean by calibrating for linear functions (2000) (113)
Comparing the shapes of regression functions (2000) (67)
Rapid adaptive evolution of colour vision in the threespine stickleback radiation (2016) (42)
Hypothesis Testing in Comparative and Experimental Studies of Function-Valued Traits (2008) (40)
Estimating and depicting the structure of a distribution of random functions (2002) (36)
Nonparametric testing for a monotone hazard function via normalized spacings (2004) (31)
Spline smoothing with model-based penalties (1997) (29)
Variation and Evolution of Function-Valued Traits (2018) (26)
Minimax Estimates in a Semiparametric Model (1988) (23)
Nonparametric Regression Estimation using Weak Separability (2001) (18)
Penalized regression, mixed effects models and appropriate modelling (2013) (17)
The theory and application of penalized methods or Reproducing Kernel Hilbert Spaces made easy (2011) (15)
Genetic Variation, Simplicity, and Evolutionary Constraints for Function-Valued Traits (2015) (15)
PAC learning in non-linear FIR models (2001) (14)
Bump hunting in regression analysis (1992) (14)
CriSP: A Tool for Bump Hunting (2001) (13)
A note on generalized cross-validation with replicates (1992) (11)
Modeling regional impacts of climate teleconnections using functional data analysis (2014) (10)
Minimax Bayes Estimation in Nonparametric Regression (1991) (9)
Functional data analysis in evolutionary biology (2003) (9)
Switching nonparametric regression models (2014) (8)
Model-based curve registration via stochastic approximation EM algorithm (2017) (8)
Modelling multi‐scale, state‐switching functional data with hidden Markov models (2021) (7)
Switching nonparametric regression models for multi‐curve data (2015) (6)
Robust design in a two treatment comparison in the presence of a covariate (1987) (6)
Analysis of aggregated functional data from mixed populations with application to energy consumption (2014) (6)
Functional Data Model for Genetically Related Individuals With Application to Cow Growth (2015) (5)
A Sequential Probability Ratio Test Using a Biased Coin Design (1985) (5)
Learning of nonlinear FIR models under uniform distribution (1999) (5)
Visualizing genetic constraints (2013) (5)
Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise (2017) (4)
Local linear extrapolation (2003) (4)
TESTING FOR MONOTONICITY OF A REGRESSION MEAN WITHOUT SELECTING A BANDWIDTH1 (1998) (4)
Application of learning theory in neural modeling of dynamic systems (2000) (4)
Nonparametric tests for bounds on the derivative of a regression function (1996) (4)
A Local Limit Theorem for a Biased Coin Design for Sequential Tests (1985) (3)
Neural ARX Models and PAC Learning (2000) (2)
Some theory for -spline smoothing (1999) (1)
Pre-averaged kernel estimators for the drift function of a diffusion process in the presence of microstructure noise (2016) (1)
Repeated significance tests with biased coin allocation schemes (1986) (1)
Switching Nonparametric Regression Models and the Motorcycle Data revisited (2013) (1)
Dimensional Analysis in Statistical Modelling (2020) (0)
Using online student focus groups in the development of new educational resources (preprint) (2023) (0)
Prinsimp (2014) (0)
Seasonal confounding and residual correlation in analyses of health effects of air pollution (2007) (0)
Modeling regional impacts of climate teleconnections using functional data analysis (2013) (0)
Modelling Multi-level Power Usage with Latent States and Smooth Functions (2015) (0)
Rapid adaptive of colour vision in the threespine stickleback radiation. (2020) (0)
Line transects of two‐dimensional random fields: Estimation and design (1997) (0)
Structured, Interactive Resources for Teaching Bayesian Inference (2022) (0)
Comments on: Dynamic relations for sparsely sampled Gaussian processes (2010) (0)
Discussion (2001) (0)
MINIMAX BAYES ESTIMATION, PENALIZED LIKELIHOOD METHODS, AND RESTRICTED MINIMAX ESTIMATION (1991) (0)

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Other Resources About Nancy E. Heckman

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What Schools Are Affiliated With Nancy E. Heckman?

Nancy E. Heckman is affiliated with the following schools: