Matthew Reimherr
Associate Professor of Statistics
-
411 Thomas Bldg
University Park, PA - mlr36@psu.edu
- 814-865-2544
Huck Affiliations
Publication Tags
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Testing Methodology Time Series Multiple Imputation Monte Carlo Simulation Phenotype Scalar Functional Data Screening Simulation Study Predictors Asthma Genotype Longitudinal Data Principal Components Functional Model Regression Genome Linear Regression Genomics Health Variable Selection Performance Framework DemonstrateMost Recent Publications
Discussion of A General Framework for Regression Modelling
Piotr Kokoszka, Matthew Reimherr, Statistical Modelling on p. 45-49
Prior sample size extensions for assessing prior impact and prior--likelihood discordance
Matthew Reimherr, Xiao-Li Meng, Dan Nicolae, Journal of the Royal Statistical Society, Series B
Nonlinear Functional Modeling Using Neural Networks
Aniruddha Rajendra Rao, Matthew Reimherr, 2023, Journal of Computational and Graphical Statistics
Optimal function-on-scalar regression over complex domains
Matthew Reimherr, Bharath Sriperumbudur, Hyun Bin Kang, 2023, Electronic Journal of Statistics on p. 156-197
A machine learning approach to classification for traders in financial markets
Isaac D. Wright, Matthew Reimherr, John Liechty, 2022, Stat
The Use of Brexpiprazole Combined With a Stimulant in Adults With Treatment-Resistant Attention-Deficit/Hyperactivity Disorder
Frederick W. Reimherr, Thomas E. Gift, Tammy A. Steans, Matthew L. Reimherr, Leon I. Rosenberg, Melissa Wilson, Barrie K. Marchant, 2022, Journal of Clinical Psychopharmacology on p. 445-453
Highly irregular functional generalized linear regression with electronic health records
Justin Petrovich, Matthew Reimherr, Carrie Daymont, 2022, Journal of the Royal Statistical Society. Series C: Applied Statistics on p. 806-833
Metabolomic profiling of stool of two-year old children from the INSIGHT study reveals links between butyrate and BMI
D Nandy, Craig SJC, J Cai, Y Tian, I Paul, J Savage, M Marini, E Hohman, M Reimherr, Andrew Patterson, K Makova, F Chiaromonte, 2022, Pediatric obesity on p. e12833
Modern multiple imputation with functional data
Aniruddha Rajendra Rao, Matthew Reimherr, 2021, Stat
Adaptive function-on-scalar regression with a smoothing elastic net
Ardalan Mirshani, Matthew Reimherr, 2021, Journal of Multivariate Analysis
Most-Cited Papers
Introduction to Functional Data Analysis
Piotr Kokoszka, Matthew Reimherr, 2017,
Determining the order of the functional autoregressive model
Piotr Kokoszka, Matthew Reimherr, 2013, Journal of Time Series Analysis on p. 116-129
Child Weight Gain Trajectories Linked To Oral Microbiota Composition
Sarah J.C. Craig, Daniel Blankenberg, Alice Carla Luisa Parodi, Ian M. Paul, Leann L. Birch, Jennifer S. Savage, Michele E. Marini, Jennifer L. Stokes, Anton Nekrutenko, Matthew Reimherr, Francesca Chiaromonte, Kateryna D. Makova, 2018, Scientific Reports
Feature screening for time-varying coefficient models with ultrahigh-dimensional longitudinal data
Wanghuan Chu, Runze Li, Matthew Reimherr, 2016, Annals of Applied Statistics on p. 596-617
A functional data analysis approach for genetic association studies
Matthew Reimherr, Dan Nicolae, 2014, Annals of Applied Statistics on p. 406-429
Asymptotic normality of the principal components of functional time series
Piotr Kokoszka, Matthew Reimherr, 2013, Stochastic Processes and their Applications on p. 1546-1562
On quantifying dependence: A framework for developing interpretable measures
Matthew Reimherr, Dan L. Nicolae, 2013, Statistical Science on p. 116-130
Coherent synthesis of genomic associations with phenotypes and home environments
Jesse R. Lasky, Brenna R. Forester, Matthew Reimherr, 2018, Molecular Ecology Notes on p. 91-106
The function-on-scalar LASSO with applications to longitudinal GWAS
Rina Foygel Barber, Matthew Reimherr, Thomas Schill, 2017, Electronic Journal of Statistics on p. 1351-1389
Testing separability of space-time functional processes
P. Constantinou, P. Kokoszka, M. Reimherr, 2017, Biometrika on p. 425-437
News Articles Featuring Matthew Reimherr
Sep 21, 2018
Mouth bacteria in toddlers may predict obesity, study says
Bacteria in a toddler's mouth might help predict later obesity, new research suggests. Scientists at Penn State University found the composition of microorganisms in the mouths of 2-year-olds offers clues to the child's future weight.
Full Article
Sep 20, 2018
Swabbing a child’s mouth for bacteria could predict how likely they are to become obese
A swab of a toddler’s mouth may predict their odds of growing into obese children, a new study suggests. Scientists at Pennsylvania State University discovered that the harmless microorganisms living in a two-year-old’s mouth were less diverse if they had gained more weight more quickly than most since birth.
Full Article
Sep 19, 2018
Child Weight Gain Trajectories Linked To Oral Microbiota Composition
Gut and oral microbiota perturbations have been observed in obese adults and adolescents; less is known about their influence on weight gain in young children.
Full Article