Matthew Reimherr

Associate Professor of Statistics

Matthew Reimherr

Huck Affiliations

Publication Tags

Testing Monte Carlo Simulation Time Series Methodology Phenotype Longitudinal Data Principal Components Simulation Study Screening Predictors Genome Genomics Asthma Genotype Performance Obesity Scalar Variable Selection Smoothing Autoregressive Model Project Management Feature Selection Separability Sample Size Polymorphism

Most Recent Papers

Discussion of A General Framework for Regression Modelling

Piotr Kokoszka, Matthew Reimherr, Statistical Modelling on p. 45-49

Feature Screening for Time-Varying Coefficient Models with Ultrahigh Dimensional Longitudinal Data

Wanghuan Chu, Runze Li, Matthew Reimherr, The Annals of Applied Statistics on p. 596-617

Adaptive function-on-scalar regression with a smoothing elastic net

Ardalan Mirshani, Matthew Reimherr, 2021, Journal of Multivariate Analysis

Prior sample size extensions for assessing prior impact and prior-likelihood discordance

Matthew Reimherr, Xiao Li Meng, Dan L. Nicolae, 2021, Journal of the Royal Statistical Society. Series B: Statistical Methodology on p. 413-437

Wender Utah Rating Scale: Psychometrics, clinical utility and implications regarding the elements of ADHD

Thomas E. Gift, Matthew L. Reimherr, Barrie K. Marchant, Tammy A. Steans, Frederick W. Reimherr, 2021, Journal of Psychiatric Research on p. 181-188

Types of adult attention-deficit/hyperactivity disorder: A replication analysis

Frederick W. Reimherr, Michael Roesler, Barrie K. Marchant, Thomas E. Gift, Wolfgang Retz, Florence Philipp-Wiegmann, Matthew L. Reimherr, 2020, Diseases of the Nervous System

Feature selection for generalized varying coefficient mixed-effect models with application to obesity gwas

Wanghuan Chu, Runze Li, Jingyuan Liu, Matthew Reimherr, 2020, Annals of Applied Statistics on p. 276-298

Private Posterior Inference Consistent with Public Information: A Case Study in Small Area Estimation from Synthetic Census Data

Jeremy Seeman, A Slavkovic, Matthew Reimherr, 2020, on p. 323-336

Private Posterior Inference Consistent with Public Information

Jeremy Seeman, Aleksandra Slavkovic, Matthew Reimherr, 2020, on p. 323-336

Modern Multiple Imputation with Functional Data

Aniruddha Rao, Matthew Reimherr, 2020, Stat on p. e331

Most-Cited Papers

Determining the order of the functional autoregressive model

Piotr Kokoszka, Matthew Reimherr, 2013, Journal of Time Series Analysis on p. 116-129

A functional data analysis approach for genetic association studies

Matthew Reimherr, Dan Nicolae, 2014, Annals of Applied Statistics on p. 406-429

On quantifying dependence

Matthew Reimherr, Dan L. Nicolae, 2013, Statistical Science on p. 116-130

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

Asymptotic normality of the principal components of functional time series

Piotr Kokoszka, Matthew Reimherr, 2013, Stochastic Processes and their Applications on p. 1546-1562

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

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

Predictability of shapes of intraday price curves

Piotr Kokoszka, Matthew Reimherr, 2013, Econometrics Journal on p. 285-308

Testing separability of space-time functional processes

P. Constantinou, P. Kokoszka, M. Reimherr, 2017, Biometrika on p. 425-437

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