Paper Citation Record · LEDGER

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling

As of 17 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2502.08102.

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pith.paper-citation-record.v1
2502.08102 v1

Coverage vector

measured 35 of 35 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation cfaa3686-bf76-498d-a9fb-7faca4ae9c92 · outbound

This paper cites an unresolved cited work.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Unresolved cited work

Reference 1

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This paper cites Status and perspectives on 100% renewable energy systems,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Status and perspectives on 100% renewable energy systems,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.616948Z

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Observation 91a7631d-ca2d-43bc-ba90-1c192fb62a47 · outbound

This paper cites Power-to-gas: Decarbonization of the European electricity system with synthetic methane,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Power-to-gas: Decarbonization of the European electricity system with synthetic methane,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.606204Z

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This paper cites PJM Website,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling PJM Website,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.595682Z

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Observation ed1c1e40-9de2-4bb2-b55c-1ea44e2ede7b · outbound

This paper cites Handbook,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Handbook,

Reference 5

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Observation fd3a0a19-a44e-461c-9daf-2e2b64409eec · outbound

This paper cites TMY - NSRDB,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling TMY - NSRDB,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.575333Z

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Observation 6bda23d5-af39-4f37-a591-aa21ce729c85 · outbound

This paper cites The 100-Year Flood,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling The 100-Year Flood,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.565504Z

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Observation b80f7f66-3083-424f-a7b3-5c2c43cf31bb · outbound

This paper cites Generating synthetic energy time series: A review,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Generating synthetic energy time series: A review,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.555231Z

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Observation b8aa245c-22ba-492a-aa02-adabd603b014 · outbound

This paper cites MCMC for Wind Power Simulation,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling MCMC for Wind Power Simulation,

Reference 9

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Observation 5a450d69-ef3f-4f3e-971b-28cc327dc1ac · outbound

This paper cites Statistical bivariate modelling of wind using first- order Markov chain and Weibull distribution,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Statistical bivariate modelling of wind using first- order Markov chain and Weibull distribution,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.534306Z

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Observation c03af75e-de5f-442b-9e8e-b7429a85f28e · outbound

This paper cites Pitfalls of modeling wind power using Markov chains,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Pitfalls of modeling wind power using Markov chains,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.523102Z

Source-reported events for the cited work

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Observation c3818bfa-d78f-4533-9ae2-8f1ee057b196 · outbound

This paper cites A new Markov-chain-related statistical approach for modelling synthetic wind power time series,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling A new Markov-chain-related statistical approach for modelling synthetic wind power time series,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.512941Z

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Observation 79881353-03e3-46b3-8cf1-f1b610d69832 · outbound

This paper cites Exploring wind energy for small off-grid power generation in remote areas of Northern Brazil,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Exploring wind energy for small off-grid power generation in remote areas of Northern Brazil,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.502690Z

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Observation 595b1de1-b76e-4e18-892d-0a27f6a3df95 · outbound

This paper cites Time-series models for reliability evaluation of power systems including wind energy,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Time-series models for reliability evaluation of power systems including wind energy,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.492486Z

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Observation 1167970f-7e4c-42b3-9d69-448b95d27b94 · outbound

This paper cites Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.480954Z

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Observation 22a71bcb-6703-45c2-842c-f075535e5c5e · outbound

This paper cites ARIMA-based time series model of stochastic wind power generation,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling ARIMA-based time series model of stochastic wind power generation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.470182Z

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Observation b2b3f810-80af-4718-84e9-064df981ef97 · outbound

This paper cites Synthesis of hourly wind power series using the Moving Block Bootstrap method,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Synthesis of hourly wind power series using the Moving Block Bootstrap method,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.459469Z

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Observation 5c8e04df-dadd-4ecf-82b4-6a697df52bc0 · outbound

This paper cites Boostrapping the Probability Distribution of Peak Electricity Demand,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Boostrapping the Probability Distribution of Peak Electricity Demand,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.449145Z

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This paper cites Forecasting the Demand for Electricity in Saudi Arabia,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Forecasting the Demand for Electricity in Saudi Arabia,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.438328Z

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Observation 75eb5e41-0568-4c06-8513-af41a3a7a79e · outbound

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Efron and R

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.427915Z

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Observation 81bd2f0e-4bc6-44af-8118-3d464f9d340a · outbound

This paper cites Bootstrap methods: A review,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Bootstrap methods: A review,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.416933Z

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Observation cfc0be13-224e-4001-82cd-338c93c9c6d1 · outbound

This paper cites Bootstrap Methods for Time Series,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Bootstrap Methods for Time Series,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.406103Z

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Observation 393b2872-8c09-4832-a2bc-7f1367c00932 · outbound

This paper cites Bootstrapping time series models,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Bootstrapping time series models,

Reference 23

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Observation 12e4393c-00b2-46b7-b44b-34a8190877f3 · outbound

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Bootstrap Methods for Time Series,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.383631Z

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Observation 5a0fd2a8-61d6-4b67-9701-818ad415454a · outbound

This paper cites A Nearest Neighbor Bootstrap for Resampling Hydrologic Time,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling A Nearest Neighbor Bootstrap for Resampling Hydrologic Time,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.372385Z

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Observation ce23845b-75e8-4462-aeb3-6ac74b86f331 · outbound

This paper cites A Symmetric Block Resampling Method to Generate Energy Time Series Data,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling A Symmetric Block Resampling Method to Generate Energy Time Series Data,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.361172Z

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling A k-nearest neighbor space-time simulator with applications to large-scale wind and solar power modeling,

Reference 27

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Confronting climate uncertainty in water re- sources planning and project design: the decision tree framework,

Reference 28

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Modeling and generating synthetic anomalies for energy and power time series,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.338318Z

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Observation a3bfa94b-86fb-4e8c-aa54-e7058a72e7f3 · outbound

This paper cites Synthetic Data Generation: A Comparative Study,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Synthetic Data Generation: A Comparative Study,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.326468Z

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Observation c7db9061-d061-4044-8c2b-04a17a15f707 · outbound

This paper cites SynSys: A Synthetic Data Generation System for Healthcare Applications,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling SynSys: A Synthetic Data Generation System for Healthcare Applications,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.314661Z

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Observation bec54026-9055-4f89-8b37-a3a4cad677de · outbound

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling The Synthetic Data Vault,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.303407Z

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Observation 131c3f09-697f-4074-a2a6-eeb84ae3c503 · outbound

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Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Sequential Models in the Synthetic Data Vault

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This paper cites Joint production and energy supply planning of an industrial microgrid,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Joint production and energy supply planning of an industrial microgrid,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.292137Z

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Observation 39560d00-59fb-4f2a-8fd1-c3d2fa8ad239 · outbound

This paper cites Representation of uncertainty in market models for operational planning and forecasting in renewable power systems: a review,.

Resampling Methods that Generate Time Series Data to Enable Sensitivity and Model Analysis in Energy Modeling Representation of uncertainty in market models for operational planning and forecasting in renewable power systems: a review,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T10:46:52.281141Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

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