Evidence map›Paper›PMID 33897300›Full record

ArticleStochastic environmental research and risk assessment : research journal2021

COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning.

Antoni Torres-Signes, María P Frías, María D Ruiz-Medina

Abstract read
In one paragraph

Article in Stochastic environmental research and risk assessment : research journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. An analytical approach to evaluate the impact of age demographics in a pandemic.Stochastic environmental research and risk assessment : research journal · 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.

Antoni Torres-SignesDepartment of Statistics and Operation Research, Faculty of Sciences, University of Málaga, Málaga, Spain.
María P FríasDepartment of Statistics and Operation Research, Faculty of Sciences, University of Jaén, Jaén, Spain.
María D Ruiz-MedinaDepartment of Statistics and Operation Research, Faculty of Sciences, University of Granada, Granada, Spain.ORCID 0000-0001-7445-7060

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function is minimized in the framework of trigonometric regression. While, in our subsequent spatial residual correlation analysis, maximization of the likelihood allows us to compute the posterior mode in a Bayesian multivariate time series soft-data framework. The presented approach is applied to the analysis of COVID-19 mortality in the first wave affecting the Spanish Communities, since March 8, 2020 until May 13, 2020. An empirical comparative study with Machine Learning (ML) regression, based on random SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00477-021-02021-0.

Indexed as

COVID-19 analysisCurve regressionHard-dataMachine learningMultivariate time seriesSoft-data

Identifiers

PMID33897300
PMCPMC8053745

What OpenQuestion holds

Textmetadata
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.