Matthew Reimherr

2.0k total citations · 1 hit paper
47 papers, 1.1k citations indexed

About

Matthew Reimherr is a scholar working on Statistics and Probability, Genetics and Artificial Intelligence. According to data from OpenAlex, Matthew Reimherr has authored 47 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Statistics and Probability, 10 papers in Genetics and 9 papers in Artificial Intelligence. Recurrent topics in Matthew Reimherr's work include Statistical Methods and Inference (16 papers), Genetic and phenotypic traits in livestock (8 papers) and Genetic Associations and Epidemiology (7 papers). Matthew Reimherr is often cited by papers focused on Statistical Methods and Inference (16 papers), Genetic and phenotypic traits in livestock (8 papers) and Genetic Associations and Epidemiology (7 papers). Matthew Reimherr collaborates with scholars based in United States, Italy and Germany. Matthew Reimherr's co-authors include Piotr Kokoszka, Alexander Aue, Dan L. Nicolae, Lajos Horváth, Runze Li, Rina Foygel Barber, Francesca Chiaromonte, Jesse R. Lasky, Brenna R. Forester and Thomas E. Gift and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Bioinformatics.

In The Last Decade

Matthew Reimherr

47 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Introduction to Functional Data Analysis

2017 302 citations Piotr Kokoszka, Matthew Reimherr profile →

Peers

Countries citing papers authored by Matthew Reimherr

Since Specialization

Citations

This map shows the geographic impact of Matthew Reimherr's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthew Reimherr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Reimherr more than expected).

Fields of papers citing papers by Matthew Reimherr

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Reimherr. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthew Reimherr. The network helps show where Matthew Reimherr may publish in the future.

Co-authorship network of co-authors of Matthew Reimherr

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Reimherr. A scholar is included among the top collaborators of Matthew Reimherr based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew Reimherr. Matthew Reimherr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Methylation profiles at birth linked to early childhood obesity 2024 ·Journal of Developmental Origins of Health and Disease ·Delphine Larivière, Sarah J. C. Craig, Ian M. Paul, Emily E. Hohman, Jennifer S. Savage, Robert O. Wright, Francesca Chiaromonte, Kateryna D. Makova, Matthew Reimherr	8
2	FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions 2024 ·Journal of Computational and Graphical Statistics ·(unknown), Lorenzo Testa, Francesca Chiaromonte, Matthew Reimherr	1
3	Nonlinear Functional Modeling Using Neural Networks 2023 ·Journal of Computational and Graphical Statistics ·(unknown), Matthew Reimherr	21
4	Optimal function-on-scalar regression over complex domains 2023 ·Electronic Journal of Statistics ·Matthew Reimherr, Bharath K. Sriperumbudur, (unknown)	3
5	A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression 2021 ·Neural Information Processing Systems ·(unknown), Matthew Reimherr, Francesca Chiaromonte	2
6	Psychometric data and versions of the Wender Utah Rating Scale including the WURS-25 & WURS-45 2021 ·SHILAP Revista de lepidopterología ·Frederick W. Reimherr, Barrie K. Marchant, Thomas E. Gift, (unknown), Matthew Reimherr	1
7	Wender Utah Rating Scale: Psychometrics, clinical utility and implications regarding the elements of ADHD 2021 ·Journal of Psychiatric Research ·Thomas E. Gift, Matthew Reimherr, Barrie K. Marchant, (unknown), Frederick W. Reimherr	10
8	Constructing a polygenic risk score for childhood obesity using functional data analysis 2021 ·Econometrics and Statistics ·Sarah J. C. Craig, (unknown), (unknown), Ian M. Paul, Leann L. Birch, Jennifer S. Savage, Michele E. Marini, Francesca Chiaromonte, Matthew Reimherr, Kateryna D. Makova	6
9	Types of Adult Attention-Deficit/Hyperactivity Disorder 2020 ·The Journal of Clinical Psychiatry ·Frederick W. Reimherr, Michael Roesler, Barrie K. Marchant, Thomas E. Gift, Wolfgang Retz, (unknown), Matthew Reimherr	35
10	Feature selection for generalized varying coefficient mixed-effect models with application to obesity GWAS 2020 ·The Annals of Applied Statistics ·(unknown), Runze Li, Jingyuan Liu, Matthew Reimherr	8
11	Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA 2019 ·arXiv (Cornell University) ·(unknown), (unknown), Matthew Reimherr, Aleksandra Slavković	4
12	Functional data analysis for computational biology 2019 ·Bioinformatics ·Marzia A. Cremona, Hongyan Xu, Kateryna D. Makova, Matthew Reimherr, Francesca Chiaromonte, Pedro Madrigal	13
13	Child Weight Gain Trajectories Linked To Oral Microbiota Composition 2018 ·Scientific Reports ·Sarah J. C. Craig, Daniel Blankenberg, (unknown), Ian M. Paul, Leann L. Birch, Jennifer S. Savage, Michele E. Marini, Jennifer L. Stokes, Anton Nekrutenko, Matthew Reimherr, Francesca Chiaromonte, Kateryna D. Makova	43
14	Simultaneous variable selection and smoothing for high-dimensional function-on-scalar regression 2018 ·Electronic Journal of Statistics ·(unknown), Matthew Reimherr	12
15	Coherent synthesis of genomic associations with phenotypes and home environments 2017 ·Molecular Ecology Resources ·Jesse R. Lasky, Brenna R. Forester, Matthew Reimherr	25
16	Asymptotic properties of principal component projections with repeated eigenvalues 2017 ·Statistics & Probability Letters ·(unknown), Matthew Reimherr	3
17	Feature screening for time-varying coefficient models with ultrahigh-dimensional longitudinal data 2016 ·The Annals of Applied Statistics ·(unknown), Runze Li, Matthew Reimherr	34
18	Determining the order of the functional autoregressive model: ORDER OF FUNCTIONAL AUTOREGRESSION 2013 ·Journal of Time Series Analysis ·Piotr Kokoszka, Matthew Reimherr	21
19	Asymptotic normality of the principal components of functional time series 2013 ·Stochastic Processes and their Applications ·Piotr Kokoszka, Matthew Reimherr	25
20	Determining the order of the functional autoregressive model 2012 ·Journal of Time Series Analysis ·Piotr Kokoszka, Matthew Reimherr	52

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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