Evidence map›Paper›PMID 37448596›Full record

ArticleTechnometrics : a journal of statistics for the physical, chemical, and engineering sciences2023

A Sharper Computational Tool for L

Xiaoqian Liu, Eric C Chi, Kenneth Lange

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Technometrics : a journal of statistics for the physical, chemical, and engineering sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Robust Low-rank Tensor Decomposition with theTechnometrics : a journal of statistics for the physical, chemical, and engineering sciences · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Xiaoqian LiuDepartment of Statistics, North Carolina State University.
Eric C ChiDepartment of Statistics, Rice University.
Kenneth LangeDepartments of Computational Medicine, Human Genetics, and Statistics University of California, Los Angeles.

Funding

STATISTICAL METHODS FOR GENE MAPPINGR01GM053275 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LANGE, KENNETH L · 1995 to 2019
$9.3M
Genomics, GPUs, and Next Generation Computational StatisticsR01HG006139 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI SOBEL, ERIC · 2011 to 2023
$5.1M
Modeling, Inference, and Optimization for Genomic and Biomedical Big DataR35GM141798 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI LANGE, KENNETH L · 2021 to 2025
$2.7M
Imputing Single Cell Rna Sequencing Data: Mathematical, Statistical And Computational ChallengesR01GM135928 · NIGMS · RICE UNIVERSITY · PI CHI, ERIC C · 2019 to 2021
$696k
Workshops on Genomics and Next Generation Computational Statistics for Big DataR25HG011845 · NHGRI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI PAPP, JEANETTE CHRISTINE, SOBEL, ERIC · 2021 to 2025
$402k
NHGRI NIH HHS R01 HG006139NHGRI NIH HHS R25 HG011845NIGMS NIH HHS R01 GM053275NIGMS NIH HHS R01 GM135928NIGMS NIH HHS R35 GM141798
6 · The paper itself

Abstract

Building on previous research of Chi and Chi (2022), the current paper revisits estimation in robust structured regression under the L

Indexed as

distance penalizationIntegral squared error criterionMM principleNewton’s methodpenalized estimation

Identifiers

PMID37448596
PMCPMC10338026

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.