<b>IncDTW</b>: An <i>R</i> Package for Incremental Calculation of Dynamic Time Warping

Leodolter, Maximilian; Plant, Claudia; Brändle, Norbert

doi:10.18637/jss.v099.i09

Cited by 8 publications

(3 citation statements)

References 20 publications

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“…We clustered CpG sites with respect to these discrete time series, and we evaluated the similarity of each pair of time series using dynamic time‐warping distance (Leodolter et al , 2021 ). Dynamic time‐warping is an algorithm that calculates the optimal matching between two time series (Liu & Muller, 2003 ; Leng & Muller, 2006 ).…”

Section: Methodsmentioning

confidence: 99%

A methylation clock model of mild SARS‐CoV‐2 infection provides insight into immune dysregulation

Mao

Miller

Nair

et al. 2023

Molecular Systems Biology

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DNA methylation comprises a cumulative record of lifetime exposures superimposed on genetically determined markers. Little is known about methylation dynamics in humans following an acute perturbation, such as infection. We characterized the temporal trajectory of blood epigenetic remodeling in 133 participants in a prospective study of young adults before, during, and after asymptomatic and mildly symptomatic SARS‐CoV‐2 infection. The differential methylation caused by asymptomatic or mildly symptomatic infections was indistinguishable. While differential gene expression largely returned to baseline levels after the virus became undetectable, some differentially methylated sites persisted for months of follow‐up, with a pattern resembling autoimmune or inflammatory disease. We leveraged these responses to construct methylation‐based machine learning models that distinguished samples from pre‐, during‐, and postinfection time periods, and quantitatively predicted the time since infection. The clinical trajectory in the young adults and in a diverse cohort with more severe outcomes was predicted by the similarity of methylation before or early after SARS‐CoV‐2 infection to the model‐defined postinfection state. Unlike the phenomenon of trained immunity, the postacute SARS‐CoV‐2 epigenetic landscape we identify is antiprotective.

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Section: Methodsmentioning

confidence: 99%

A methylation clock model of mild SARS‐CoV‐2 infection provides insight into immune dysregulation

Mao

Miller

Nair

et al. 2023

Molecular Systems Biology

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“…Additionally, DTW can be applied to detect and cope with different speeds and time deformations associated with time-dependent data. Recently, the R package IncDTW based on the DTW improved the possibilities to classify time series or clusters [93]. To analyze in detail the influence of each variable, Figure 14 shows the truncated histogram for these simulations using discrepancies based on MAPE and DTW metrics.…”

Section: Resultsmentioning

confidence: 99%

Sensitive Parameter Analysis for Solar Irradiance Short-Term Forecasting: Application to LoRa-Based Monitoring Technology

Bueso

Paredes-Parra

Mateo-Aroca

et al. 2022

Sensors

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Due to the relevant penetration of solar PV power plants, an accurate power generation forecasting of these installations is crucial to provide both reliability and stability of current grids. At the same time, PV monitoring requirements are more and more demanded by different agents to provide reliable information regarding performances, efficiencies, and possible predictive maintenance tasks. Under this framework, this paper proposes a methodology to evaluate different LoRa-based PV monitoring architectures and node layouts in terms of short-term solar power generation forecasting. A random forest model is proposed as forecasting method, simplifying the forecasting problem especially when the time series exhibits heteroscedasticity, nonstationarity, and multiple seasonal cycles. This approach provides a sensitive analysis of LoRa parameters in terms of node layout, loss of data, spreading factor and short time intervals to evaluate their influence on PV forecasting accuracy. A case example located in the southeast of Spain is included in the paper to evaluate the proposed analysis. This methodology is applicable to other locations, as well as different LoRa configurations, parameters, and networks structures; providing detailed analysis regarding PV monitoring performances and short-term PV generation forecasting discrepancies.

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“…However, R evolved, and many efforts were made to develop R packages that could help in multiple disciplines. Some examples include the works of [2][3][4], as well as the R packages for environmental scientists, engineers, and regulators described in [5]. Among the several works found in the literature that deal with the use of R to solve statistical problems [6], there are some that explore statistics from different perspectives.…”

Section: Introductionmentioning

confidence: 99%

LearningRlab: Educational R Package for Statistics in Computer Science Engineering

Cuadrado-Gallego,

Gómez,

Tayebi

et al. 2023

Sustainability

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This paper describes and evaluates the educational interest of LearningRlab, an educational R package developed for teaching statistics in computer science engineering. The package was developed by final degree project students to be used as an educational environment for statistics students who evaluated the package and provided feedback for future versions. Such a process increases the motivation of both groups of students. This paper presents how the use of the R packages conceived and developed for engineering education can improve the learning process in the computer science engineering bachelor’s degree. Two different evaluations, one performed by a group of statistics students, and the other performed by final degree project students, were used to evaluate the impact on the learning process of the first version of the package to develop the second version of the package, which corrects and enhances the first version. The evaluation results show a positive effect on the learning process in both subjects. The analysis of the learning outcomes reflected in the grades of the experimental and control groups demonstrates that LearningRlab can be used as a teaching aid for statistics and final degree project subjects of the computer science engineering degree. The average laboratory grade of the students who used the package (5.76) was noticeably higher than the average laboratory grade of students who did not use it (1.84).

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IncDTW: An R Package for Incremental Calculation of Dynamic Time Warping

Cited by 8 publications

References 20 publications

A methylation clock model of mild SARS‐CoV‐2 infection provides insight into immune dysregulation

A methylation clock model of mild SARS‐CoV‐2 infection provides insight into immune dysregulation

Sensitive Parameter Analysis for Solar Irradiance Short-Term Forecasting: Application to LoRa-Based Monitoring Technology

LearningRlab: Educational R Package for Statistics in Computer Science Engineering

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