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Distributed lag non‐linear models [PDF]
Statistics in Medicine, 2010 AbstractEnvironmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure–response relationship. Here we develop the family of distributed lag non‐linear models (DLNM), a modelling framework that can simultaneously represent non‐
Gasparrini, A, Armstrong, B, Kenward, MG
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Almon-KL estimator for the distributed lag model
Arab Journal of Basic and Applied Sciences, 2021 The Almon technique is widely used to estimate the parameters of the distributed lag model (DLM). The technique suffers a setback from the challenge of multicollinearity because the explanatory variables and their lagged values are often correlated.
Adewale F. Lukman, Golam B. M. Kibria
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dLagM: An R package for distributed lag models and ARDL bounds testing.
PLoS ONE, 2020 In this article, we introduce the R package dLagM for the implementation of distributed lag models and autoregressive distributed lag (ARDL) bounds testing to explore the short and long-run relationships between dependent and independent time series ...
Haydar Demirhan
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Multiple exposure distributed lag models with variable selection. [PDF]
Biostatistics, 2023 Distributed lag models are useful in environmental epidemiology as they allow the user to investigate critical windows of exposure, defined as the time periods during which exposure to a pollutant adversely affects health outcomes.
Antonelli J, Wilson A, Coull BA.
europepmc +3 more sources
Natural resources forum (Print), 2023 This study explores the impact of natural resource exploitation, trade openness, and economic growth on carbon emissions in a sample of oil‐exporting nations for the period 1971–2014.
Tarek Ghazouani, Samir Maktouf
semanticscholar +1 more source
Environmental science and pollution research international, 2023 There has been a plethora of debate on the link between fiscal decentralization and a drop in carbon dioxide (CO_2) emissions, even though the evidence supporting this assertion is relatively sparse.
Maxwell Chukwudi Udeagha, M. Breitenbach
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Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling. [PDF]
Int J EpidemiolBackground Distributed lag non-linear models (DLNMs) are the reference framework for modelling lagged non-linear associations. They are usually used in large-scale multi-location studies. Attempts to study these associations in small areas either did not
Quijal-Zamorano M +3 more
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Recent developments of the autoregressive distributed lag modelling framework
Journal of economic surveys (Print), 2021 We review the literature on the Autoregressive Distributed Lag (ARDL) model, from its origins in the analysis of autocorrelated trend stationary processes to its subsequent applications in the analysis of cointegrated non-stationary time series.
J. Cho +2 more
semanticscholar +1 more source
Inflation forecasting using autoregressive distributed lag (ARDL) models
Jurnal Ekonomi & Studi Pembangunan, 2023 This study attempts to evaluate and compare the inflation-predicting performance of several ARDL models. Since there was no cointegration, the ARDL model does not employ an error correction term.
Regi Muzio Ponziani
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