ArticleMethodsX2020
How to apply the novel dynamic ARDL simulations (dynardl) and Kernel-based regularized least squares (krls).
Article in MethodsX, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Environmental sustainability in Somalia: the role of clean cooking energy and remittances on ecological footprints.Scientific reports · 2026Article
- Assessing food security and environmental quality under policy stringency and geopolitics using counterfactual and machine learning approaches.Scientific reports · 2026Article
- Impact of Climate Change, Agricultural Credit and Inflation on Cereal Crop Productivity in Ethiopia: Novel Dynamic Simulated ARDL Approach.Food science & nutrition · 2026Article
- Article
- Article
- Unravelling the dynamics of human development and economic growth on crude oil production based on ARDL and NARDL models.MethodsX · 2023Article
- Turning points for environmental sustainability: the potential role of income inequality, human capital, and globalization.Environmental science and pollution research international · 2022Article
- Dataset on bitcoin carbon footprint and energy consumption.Data in brief · 2022Article
- The role of electricity consumption, capital, labor force, carbon emissions on economic growth: implication for environmental sustainability targets in Nigeria.Environmental science and pollution research international · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of dynamic Autoregressive Distributed Lag (dynardl) simulations and Kernel-based Regularized Least Squares (krls) to time series data is gradually gaining recognition in energy, environmental and health economics. The Kernel-based Regularized Least Squares technique is a simplified machine learning-based algorithm with strength in its interpretation and accounting for heterogeneity, additivity and nonlinear effects. The novel dynamic ARDL Simulations algorithm is useful for testing cointegration, long and short-run equilibrium relationships in both levels and differences. Advantageously, the novel dynamic ARDL Simulations has visualization interface to examine the possible counterfactual change in the desired variable based on the notion of
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.