J. Marron

J. Marron, B. Reed, Su Zhang, 2012, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

Object Oriented Data Analysis of Cell-Well Structured Data

J. Marron, P. Haaland, Xiaosun Lu, 2013, 1303.4767.

A Backward Generalization of PCA for Image Analysis

J. Marron, S. Pizer, Sungkyu Jung, 2010 .

ective writing in mathematical statistics

J. Marron, 1999 .

SiZer for length biased, censored density and hazard estimation

James Stephen Marron, Jacobo de Uña-Álvarez, J. Marron, 2004 .

SCISSOR: a framework for identifying structural changes in RNA transcripts

J. Marron, D. Hayes, K. Hoadley, 2021, Nature communications.

Variable screening based on Gaussian Centered L-moments

J. Marron, H. Oja, Kai Zhang, 2019, Comput. Stat. Data Anal..

Object shape representation via skeletal models (s-reps) and statistical analysis

J. Marron, S. Pizer, J. Damon, 2020 .

Discrimination of Kelvin Materials via ARFI Response

J. Marron, M. Haider, C. Gallippi, 2006 .

Trends in Northern Hemispheric Snow Presence

J. Marron, J. Woody, J. Dyer, 2022, Journal of Hydrometeorology.

Mini-Workshop: Asymptotic Statistics on Stratified Spaces

J. Marron, Ezra Miller, S. Huckemann, 2014 .

Object-Oriented Data Analysis of Cell Images

James Stephen Marron, Perry D. Haaland, Xiaosun Lu, 2014 .

Significance Testing in Clustering

Andrew B. Nobel, James Stephen Marron, Christian Hennig, 2015 .

High Dimensional Asymptotics

J. Marron, I. Dryden, 2021, Object Oriented Data Analysis.

Variable window width kernel estimates of probability densities

James Stephen Marron, Peter Hall, J. Marron, 1992 .

High Dimensional Principal Component Scores and Data Visualization

J. Marron, Haipeng Shen, D. Shen, 2012, 1211.2679.

How Far Are Automatically Chosen Regression Smoothing Parameters From Their Optimum?: Rejoinder

W. Härdle, J. Marron, P. Hall, 1988 .

Discussion of large covariance estimation by thresholding principal orthogonal complements

J. Marron, Yufeng Liu, Haipeng Shen, 2013 .

Methods for quantitative characterization of bone injury from computed-tomography images

Beatriz Paniagua, J. S. Marron, Eric Livingston, 2019, Medical Imaging.

Distance‐weighted discrimination of face images for gender classification pdf

J. S. Marron, Mónica Benito, Eduardo García-Portugués, 2017, ArXiv.

Mixed-Model Functional ANOVA for Studying Human Tactile Perception

James Stephen Marron, Dan J. Spitzner, G. Essick, 2003 .

A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium.

J. Marron, T. Schwartz, L. Callahan, 2019, Osteoarthritis and cartilage.

Analysis of juggling data: Object oriented data analysis of clustering in acceleration functions

J. Marron, Xiaosun Lu, 2014 .

BlackOPs: increasing confidence in variant detection through mappability filtering

J. S. Marron, Jinze Liu, Matthew D. Wilkerson, 2013, Nucleic acids research.

Support vector machine for data on manifolds: An application to image analysis

Martin Styner, J. S. Marron, Mark Foskey, 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Statistical significance for hierarchical clustering

Yufeng Liu, Patrick K. Kimes, David Neil Hayes, 2014, Biometrics.

Adjustment of systematic microarray data biases

Joel S. Parker, Dong Xiang, J. S. Marron, 2004, Bioinform..

A method for normalizing histology slides for quantitative analysis

J. S. Marron, David Borland, Xiaojun Guan, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Asymptotics of hierarchical clustering for growing dimension

J. S. Marron, Jan Hannig, Petro Borysov, 2014, J. Multivar. Anal..

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

B. H. Miller, J. Marron, Sean Skwerer, 2011, Psychopharmacology.

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

Heather D. Couture, Lindsay A. Williams, J. Marron, 2018, npj Breast Cancer.

Statistical Significance of Clustering Using Soft Thresholding

Yufeng Liu, Ming Yuan, Hanwen Huang, 2013, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

JOINT AND INDIVIDUAL ANALYSIS OF BREAST CANCER HISTOLOGIC IMAGES AND GENOMIC COVARIATES.

Heather D. Couture, J. Marron, C. Perou, 2019, The annals of applied statistics.

ReQON: a Bioconductor package for recalibrating quality scores from next-generation sequencing data

Joel S. Parker, J. S. Marron, Matthew D. Wilkerson, 2012, BMC Bioinformatics.

Speculation on the generality of the backward stepwise view of PCA

J. S. Marron, Ian L. Dryden, Sungkyu Jung, 2010, MIR '10.

Large‐margin classification with multiple decision rules pdf

Yufeng Liu, J. S. Marron, D. Neil Hayes, 2014, Stat. Anal. Data Min..

R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment

Yufeng Liu, J. S. Marron, Xiaosun Lu, 2012, Bioinform..

Variable heavy tails in Internet traffic

Gennady Samorodnitsky, J. S. Marron, F. Donelson Smith, 2004, Perform. Evaluation.

Functional Data Analysis of Amplitude and Phase Variation

J. S. Marron, Anuj Srivastava, James O. Ramsay, 2015, 1512.03216.

Regression smoothing parameters that are not far from their optimum

James Stephen Marron, Wolfgang Karl Härdle, Peter Hall, 1992 .

JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES.

Eric F Lock, Andrew B Nobel, Katherine A Hoadley, 2011, The annals of applied statistics.

Non-linear Hypothesis Testing of Geometric Object Properties of Shapes Applied to Hippocampi

J. S. Marron, Fred Godtliebsen, Stephen M. Pizer, 2015, Journal of Mathematical Imaging and Vision.

Multi-Object Analysis of Volume, Pose, and Shape Using Statistical Discrimination

Martin Styner, Guido Gerig, J. S. Marron, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Statistical Shape Analysis of Multi-Object Complexes

Martin Styner, Guido Gerig, J. S. Marron, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

Discrimination analysis using multi-object statistics of shape and pose

Martin Styner, Guido Gerig, J. S. Marron, 2007, SPIE Medical Imaging.

Sizer for smoothing splines

James Stephen Marron, Jin-Ting Zhang, J. Marron, 2005, Comput. Stat..

Sticky central limit theorems on open books

J. S. Marron, Ezra Miller, Jonathan C. Mattingly, 2012, 1202.4267.

Curvature vs. Slope Inference for Features in Nonparametric Curve Estimates

J. S. Marron, P. Chaudhuri, J. Marron, 2002 .

Significance in scale-space for clustering

Fred Godtliebsen, James Stephen Marron, Stephen M. Pizer, 2002 .

Some asymptotics for multimodality tests based on kernel density estimates

James Stephen Marron, Nicholas I. Fisher, Enno Mammen, 1992 .

Interactive local bandwidth choice

J. S. Marron, F. Udina, J. Marron, 1999, Stat. Comput..

Uniform consistency of automatic and location-adaptive delta-sequence estimators

J. Marron, D. Nolan, 1989 .

Fast and simple scatterplot smoothing

James Stephen Marron, Wolfgang Karl Härdle, W. Härdle, 1995 .

Angle-based joint and individual variation explained

J. S. Marron, Jan Hannig, Qing Feng, 2017, J. Multivar. Anal..

Mass recentred kernel smoothers

E. Mammen, J. Marron, 1997 .

Choosing a Kernel Regression Estimator

James Stephen Marron, C. K. Chu, J. Marron, 1991 .

Semiparametric Comparison of Regression Curves

James Stephen Marron, Wolfgang Härdle, W. Härdle, 1990 .

Random approximations to some measures of accuracy in nonparametric curve estimation

James Stephen Marron, Wolfgang Härdle, W. Härdle, 1986 .

Visual Error Criteria for Qualitative Smoothing

James Stephen Marron, Alexandre B. Tsybakov, A. Tsybakov, 1995 .

Convergence properties of an empirical error criterion for multivariate density estimation

James Stephen Marron, J. Marron, 1986 .

Asymptotically Optimal Bandwidth Selection for Kernel Density Estimators from Randomly Right-Censored Samples.

James Stephen Marron, W. J. Padgett, J. Marron, 1987 .

Semi-parametric multivariate modelling when the marginals are the same

J. Marron, V. Pérez-Abreu, Miguel Nakamura, 2003 .

Least squares sieve estimation of mixture distributions with boundary effects

Ling Wang, Haipeng Shen, James Stephen Marron, 2015 .

A General Framework for Constrained Smoothing

E. Mammen, B. Turlach, M. Wand, 1998 .

MultiResolution Anomaly Detection Method for Long Range Dependent Time Series

Zhengyuan Zhu, J. S. Marron, J. Marron, 2008, 0809.1281.

Multi-Resolution Anomaly Detection for the internet

Zhengyuan Zhu, Lingsong Zhang, K. Jeffay, 2008, IEEE INFOCOM Workshops 2008.

Bootstrap bandwidth selection

J. Stephen Marron, J. Marron, 1990 .

Scaled Torus Principal Component Analysis

J. S. Marron, Eduardo Garc'ia-Portugu'es, Pavlos Zoubouloglou, 2021, Journal of Computational and Graphical Statistics.

Quantifying anatomical shape variations in neurological disorders

Michael Weiner, P. Thomas Fletcher, J. S. Marron, 2014, Medical Image Anal..

Data science vs. statistics: two cultures?

J. S. Marron, Iain Carmichael, J. Marron, 2017, Japanese Journal of Statistics and Data Science.

Direction-Projection-Permutation for High-Dimensional Hypothesis Tests

J. S. Marron, Chihoon Lee, Susan Wei, 2013, 1304.0796.

Non-Euclidean Analysis of Joint Variations in Multi-Object Shapes pdf

Martin Styner, J. S. Marron, James Damon, 2021, ArXiv.

Nested Sphere Statistics of Skeletal Models

J. S. Marron, Stephen M. Pizer, Ritwik Chaudhuri, 2013, Innovations for Shape Analysis, Models and Algorithms.

New Approaches to Principal Component Analysis for Trees

J. S. Marron, Gábor Pataki, Elizabeth Bullitt, 2012, Statistics in Biosciences.

A Principal Component Analysis for Trees

Gabor Pataki, Elizabeth Bullitt, Haonan Wang, 2008, 0810.0944.

The negative correlations between data-determined bandwidths and the optimal bandwidth

J. Marron, Shean-Tsong Chiu, 1990 .

Does Code Decay? Assessing the Evidence from Change Management Data

Audris Mockus, J. S. Marron, Alan F. Karr, 2001, IEEE Trans. Software Eng..

Backwards Principal Component Analysis and Principal Nested Relations

J. S. Marron, James N. Damon, J. Marron, 2014, Journal of Mathematical Imaging and Vision.

Intuitive, Localized Analysis of Shape Variability

Paul A. Yushkevich, J. S. Marron, Stephen M. Pizer, 2001, IPMI.

Multiscale deformable model segmentation and statistical shape analysis using medial descriptions

Paul A. Yushkevich, P. Thomas Fletcher, J. S. Marron, 2002, IEEE Transactions on Medical Imaging.

Iterated Transformation–Kernel Density Estimation

James Stephen Marron, Lijian Yang, J. Marron, 1999 .

Fast and Simple Scatterplot

J. Marron, SmoothingbyW, .. H. ardle, 1994 .

Appearance normalization of histology slides

J. S. Marron, David Borland, Marc Niethammer, 2015, Comput. Medical Imaging Graph..

A FUNCTIONAL DATA ANALYSIS APPROACH FOR EVALUATING TEMPORAL PHYSIOLOGIC RESPONSES TO PARTICULATE MATTER

J. S. Marron, Chihoon Lee, Daniel L. Costa, 2007 .

Simultaneous Density Estimation of Several Income Distributions

J. Marron, H. Schmitz, 1992, Econometric Theory.

EXTREMAL DEPENDENCE: INTERNET TRAFFIC APPLICATIONS

J. S. Marron, Kevin Jeffay, Sidney I. Resnick, 2005 .

Variable heavy tailed durations in Internet traffic. Part I. Understanding heavy tails

Gennady Samorodnitsky, J. S. Marron, F. Donelson Smith, 2002, Proceedings. 10th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunications Systems.

Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

J. S. Marron, Marc Niethammer, Melissa A. Troester, 2018, MICCAI.

Predicting Fault Incidence Using Software Change History

Harvey P. Siy, J. S. Marron, Alan F. Karr, 2000, IEEE Trans. Software Eng..

Nested nonnegative cone analysis pdf

J. S. Marron, Lingsong Zhang, Shu Lu, 2013, Comput. Stat. Data Anal..

Principal arc analysis on direct product manifolds

J. S. Marron, Sungkyu Jung, Mark Foskey, 2011, 1104.3472.

Long-range dependence analysis of Internet traffic

Zhengyuan Zhu, James Stephen Marron, Vladas Pipiras, 2011 .

Robust Centroid Quantile Based Classi Þ cation for High Dimension Low Sample Size Data

J. Marron, Jiancheng Jiang, 2003 .

Geometric Insights into Support Vector Machine Behavior using the KKT Conditions pdf

J. S. Marron, Iain Carmichael, J. Marron, 2017, Electronic Journal of Statistics.

Efficiency clustering for low-density microarrays and its application to QPCR

J. S. Marron, Eric F. Lock, Dirk P. Dittmer, 2010, BMC Bioinformatics.

Boundary behavior in High Dimension, Low Sample Size asymptotics of PCA

J. S. Marron, Sungkyu Jung, Arusharka Sen, 2012, J. Multivar. Anal..

Multivariate Statistical Analysis of Deformation Momenta Relating Anatomical Shape to Neuropsychological Measures

P. Thomas Fletcher, J. S. Marron, Sarang C. Joshi, 2010, MICCAI.

Comparison of binary discrimination methods for high dimension low sample size data

J. S. Marron, A. Bolivar-Cime, J. Marron, 2013, J. Multivar. Anal..

Statistics of time warpings and phase variations

J. Marron, J. Ramsay, Anuj Srivastava, 2014 .

Analysis of spike train data: Comparison between the real and the simulated data

James Stephen Marron, Xiaosun Lu, J. Marron, 2014 .

A simple root n bandwidth selector

James Stephen Marron, M. C. Jones, Byeong U. Park, 1991 .

Minimax efficiency of local polynomial fit estimators at boundaries

Ming-Yen Cheng, J. Stephen Marron, Jianqing Fan, 1993 .

Image and statistical analysis of melanocytic histology

David Borland, James Stephen Marron, Marc Niethammer, 2012, Histopathology.

On partial local smoothing rules for curve estimation

D. M. Titterington, J. Stephen Marron, Peter Hall, 1995 .

A General Framework for Consistency of Principal Component Analysis

Dan Shen, Haipeng Shen, J. S. Marron, 2012, J. Mach. Learn. Res..

The functional data analysis view of longitudinal data

Xin Zhao, James Stephen Marron, Martin T. Wells, 2004 .

dr4pl: A Stable Convergence Algorithm for the 4 Parameter Logistic Model

Hyowon An, J. S. Marron, Dirk P. Dittmer, 2019, R J..

Bandwidth Choice for Average Derivative Estimation

A. Tsybakov, W. Härdle, J. Marron, 1992 .

P2E-3 Blind Source Separation and K-Means Clustering for Vascular ARFI Image Segmentation, In Vivo and Ex Vivo

F.R. Mauldin, J.H. Levy, R.H. Behler, 2006, 2006 IEEE Ultrasonics Symposium.

Bootstrap selection of the smoothing parameter in nonparametric hazard rate estimation

James Stephen Marron, Wenceslao González-Manteiga, Ricardo Cao, 1996 .

Some heuristics of kernel based estimators of ratio functions

James Stephen Marron, Prakash N. Patil, M. T. Wells, 1994 .

Transformations to reduce boundary bias in kernel density estimation

J. Marron, D. Ruppert, 1994 .

Persistent topology of protein space

J. Marron, T. Hamelryck, J. Borgert, 2021, 2102.06768.

New Perspectives on Centering

J. S. Marron, Jan Hannig, Jack B. Prothero, 2021, The New England Journal of Statistics in Data Science.

Smoothness Independent Optimal Estimation of a Not Too Smooth Density

J. Marron, 2022 .

Geometric representation of high dimension, low sample size data

J. S. Marron, J. Marron, P. Hall, 2005 .

Topological Descriptors of Histology Images

J. S. Marron, Marc Niethammer, Charles M. Perou, 2014, MLMI.

Object oriented data analysis: Sets of trees

J. Marron, Haonan Wang, 2007 .

Comments on: Data science, big data and statistics

James Stephen Marron, J. Marron, 2019, TEST.

Data science vs. statistics: two cultures?

J. S. Marron, J. Marron, Iain Carmichael, 2018, Japanese Journal of Statistics and Data Science.

Statistical atlas construction via weighted functional boxplots

J. S. Marron, Marc Niethammer, Yi Hong, 2014, Medical Image Anal..

Functional Data Analysis of Tree Data Objects

Shankar Bhamidi, Yongdai Kim, Dan Shen, 2014, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

Analyzing Collaborative Forecast and Response Networks

J. S. Marron, Burcu Aydin, J. Marron, 2013, 1306.2062.

Principal Nested Spheres for Time Warped Functional Data Analysis

J. S. Marron, Xiaosun Lu, Qunqun Yu, 2013, 1304.6789.

Visualizing the structure of large trees

Gabor Pataki, Elizabeth Bullitt, Burcu Aydin, 2010, 1001.0951.

The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics.

Hongtu Zhu, Haipeng Shen, Dan Shen, 2016, Statistica Sinica.

Visual analysis of Spanish male mortality

J. Marron, 2015 .

Robust principal component analysis for functional data

A. M. Aguilera, Jianqing Fan, J. Marron, 1999 .