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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Hybrid Forecasting for Functional Time Series of Dissolved Oxygen Profiles |
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Identification Number: |
doi:10.7910/DVN/JNLT1S |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2023-08-01 |
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Version: |
1 |
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Bibliographic Citation: |
Durell, Luke; Scott, J. Thad; Hering, Amanda S., 2023, "Replication Data for: Hybrid Forecasting for Functional Time Series of Dissolved Oxygen Profiles", https://doi.org/10.7910/DVN/JNLT1S, Harvard Dataverse, V1 |
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Citation |
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Title: |
Replication Data for: Hybrid Forecasting for Functional Time Series of Dissolved Oxygen Profiles |
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Identification Number: |
doi:10.7910/DVN/JNLT1S |
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Authoring Entity: |
Durell, Luke (Baylor University) |
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Scott, J. Thad (Baylor University) |
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Hering, Amanda S. (Baylor University) |
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Grant Number: |
HDR:DSC 1924146 |
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Grant Number: |
HDR:DSC 1924146 |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Hering, Amanda S. |
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Access Authority: |
Durell, Luke |
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Depositor: |
Durell, Luke |
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Date of Deposit: |
2023-05-06 |
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Holdings Information: |
https://doi.org/10.7910/DVN/JNLT1S |
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Study Scope |
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Keywords: |
Earth and Environmental Sciences, Mathematical Sciences |
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Abstract: |
Supplemental code and data to reproduce the model results in Durell, L., Scott, J. T., and Hering, A. S. “Hybrid Forecasting for Functional Time Series of Dissolved Oxygen Profiles”. Data Science in Science, 2:1, DOI: 10.1080/26941899.2022.2152401 |
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Methodology and Processing |
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Sources Statement |
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Data Sources: |
Water quality vertical profile data were collected in 2019 from Eagle Mountain Lake by Dr. J. Thad Scott with support from the Tarrant Regional Water District. |
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Data Access |
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Notes: |
This dataset is to be published under a CC BY-NC-ND 4.0 license: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Bibliographic Citation: |
Durell, L., Scott, J. T., and Hering, A. S. “Hybrid Forecasting for Functional Time Series of Dissolved Oxygen Profiles”. Data Science in Science, 2:1, DOI: 10.1080/26941899.2022.2152401 |
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10a_eval_models.R |
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11_eval_models_xtable.R |
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12_eval_pred_bands_coverage.R |
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13_forecast_plots.R |
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14_profile_plots.R |
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