Evidence map›Paper›PMID 36186917›Full record

ArticleJournal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America2021

Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty.

Danielle Sass, Bo Li, Brian J Reich

Abstract read
In one paragraph

Article in Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Distributed Inference for Spatial Extremes Modeling in High Dimensions.Journal of the American Statistical Association · 2024
    Article
  2. 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.

Danielle SassUniversity of Illinois at Urbana-Champaign.
Bo LiUniversity of Illinois at Urbana-Champaign.
Brian J ReichNorth Carolina State University.

Funding

Data Integration Methods for Environmental Exposures with Applications to Air Pollution and Asthma MorbidityR01ES027892 · NIEHS · EMORY UNIVERSITY · PI CHANG, HOWARD H · 2017 to 2021
$2.7M
NIEHS NIH HHS R01 ES027892
6 · The paper itself

Abstract

Spatial extremes are common for climate data as the observations are usually referenced by geographic locations and dependent when they are nearby. An important goal of extremes modeling is to estimate the

Indexed as

fused lassofused ridgegeneralized extreme value distributiongeneralized Pareto distributionspatial extremes

Identifiers

PMID36186917
PMCPMC9524507

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.