Metraipolis › archive › dc_181fb6efeb29

Uncovering the Time-Frequency Relationship Between Google Trends and COVID-19 Vaccination Metrics: A Hybrid ARDL-Wavelet Coherence Model for Prediction — Europe PMC PMID:41140996

Source: Europe PMC (en)
Original: https://europepmc.org/article/MED/41140996
DOI: 10.7759/cureus.93193
License (as archived): solo-consultazione
Archived: 2026-11-09T18:14:06.364Z
SHA-256 of the archived text: 3600889efc8ca2cf75cf17132b62f5d3daa79b97d2baf10f3e58a541edb479df
Stable URL of this page: https://metraipolis.com/documento/dc_181fb6efeb29

How to cite

Uncovering the Time-Frequency Relationship Between Google Trends and COVID-19 Vaccination Metrics: A Hybrid ARDL-Wavelet Coherence Model for Prediction — Europe PMC PMID:41140996 — Europe PMC (en), https://europepmc.org/article/MED/41140996 (solo-consultazione); archived copy: https://metraipolis.com/documento/dc_181fb6efeb29 (Metraipolis archive dc_181fb6efeb29, sha256 3600889efc8ca2cf75cf17132b62f5d3daa79b97d2baf10f3e58a541edb479df)

BibTeX

@misc{dc181fb6efeb29,
  title = {Uncovering the Time-Frequency Relationship Between Google Trends and COVID-19 Vaccination Metrics: A Hybrid ARDL-Wavelet Coherence Model for Prediction — Europe PMC PMID:41140996},
  howpublished = {Europe PMC (en)},
  url = {https://europepmc.org/article/MED/41140996},
  note = {License solo-consultazione; archived copy https://metraipolis.com/documento/dc_181fb6efeb29; sha256 3600889efc8ca2cf75cf17132b62f5d3daa79b97d2baf10f3e58a541edb479df},
  year = {2026}
}

Archived text

The text is not reproduced here: the archive holds it as solo-consultazione (consultation only, no republication). Read it at the original source: https://europepmc.org/article/MED/41140996. Agents can read the archived copy with the MCP tool read_document.