Evidence map›Paper›PMID 34206409›Full record

ArticleEntropy (Basel, Switzerland)2021

Extreme Value Theory in Application to Delivery Delays.

Marcin Fałdziński, Magdalena Osińska, Wojciech Zalewski

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. 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.

Marcin FałdzińskiDepartment of Econometrics and Statistics, Nicolaus Copernicus University, Gagarina 11, 87-100 Toruń, Poland.ORCID 0000-0002-6236-8500
Magdalena OsińskaDepartment of Economics, Nicolaus Copernicus University, Gagarina 11, 87-100 Toruń, Poland.ORCID 0000-0002-9796-2892
Wojciech ZalewskiDepartment of Logistics, Nicolaus Copernicus University, Gagarina 11, 87-100 Toruń, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper uses the Extreme Value Theory (EVT) to model the rare events that appear as delivery delays in road transport. Transport delivery delays occur stochastically. Therefore, modeling such events should be done using appropriate tools due to the economic consequences of these extreme events. Additionally, we provide the estimates of the extremal index and the return level with the confidence interval to describe the clustering behavior of rare events in deliveries. The Generalized Extreme Value Distribution (GEV) parameters are estimated using the maximum likelihood method and the penalized maximum likelihood method for better small-sample properties. The findings demonstrate the advantages of EVT-based prediction and its readiness for application.

Indexed as

Extreme Value Theory (EVT)informationintelligent transport system (ITS)rare eventsreturn level

Identifiers

PMID34206409
PMCPMC8304894

What OpenQuestion holds

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Registered trials

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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.