Evidence map›Paper›PMID 28076654›Full record

ArticleBiometrics2017

Estimating varying coefficients for partial differential equation models.

Xinyu Zhang, Jiguo Cao, Raymond J Carroll

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biometrics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xinyu ZhangAcademy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China and Statistics and Mathematics College, Yunnan University of Finance and Economics, Kunming 650221, China.
Jiguo CaoDepartment of Statistics and Actuarial Science, Simon Fraser University, Burnaby, British Columbia, V5A1S6, Canada.
Raymond J CarrollDepartment of Statistics, Texas A&M University, 3143 TAMU, College Station, Texas 77843-3143, U.S.A.

Funding

Measurement Error, Nutrition, Physical Activity and CancerU01CA057030 · NCI · TEXAS A&M UNIVERSITY · PI CARROLL, RAYMOND J. · 2015 to 2019
$2.8M
NCI NIH HHS U01 CA057030
6 · The paper itself

Abstract

Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data.

Indexed as

Models, TheoreticalComputer SimulationB-splinesDynamical modelsInverse problemsLIDAR dataParameter cascadingSystem identification

Identifiers

PMID28076654
PMCPMC5505821

What OpenQuestion holds

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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.