Parametric and Nonparametric Sequential Change Detection in <i>R</i>: The <b>cpm</b> Package

Ross, Gordon J.

doi:10.18637/jss.v066.i03

Cited by 152 publications

(74 citation statements)

References 34 publications

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“…The moving average was calculated using the R-package 'forecast' [54]. In addition to the overall linear trend, a single change point detection has been applied using the R-package 'cpm' to find erratic changes in the mean of the data sequences [55].…”

Section: Temporal Trend Analysismentioning

confidence: 99%

Central Asia’s Changing Climate: How Temperature and Precipitation Have Changed across Time, Space, and Altitude

Haag

Jones

Samimi

2019

Climate

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Changes in climate can be favorable as well as detrimental for natural and anthropogenic systems. Temperatures in Central Asia have risen significantly within the last decades whereas mean precipitation remains almost unchanged. However, climatic trends can vary greatly between different subregions, across altitudinal levels, and within seasons. Investigating in the seasonally and spatially differentiated trend characteristics amplifies the knowledge of regional climate change and fosters the understanding of potential impacts on social, ecological, and natural systems. Considering the known limitations of available climate data in this region, this study combines both high-resolution and long-term records to achieve the best possible results. Temperature and precipitation data were analyzed using Climatic Research Unit (CRU) TS 4.01 and NASA’s Tropical Rainfall Measuring Mission (TRMM) 3B43. To study long-term trends and low-frequency variations, we performed a linear trend analysis and compiled anomaly time series and regional grid-based trend maps. The results show a strong increase in temperature, almost uniform across the topographically complex study site, with particular maxima in winter and spring. Precipitation depicts minor positive trends, except for spring when precipitation is decreasing. Expected differences in the development of temperature and precipitation between mountain areas and plains could not be detected.

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Section: Temporal Trend Analysismentioning

confidence: 99%

Central Asia’s Changing Climate: How Temperature and Precipitation Have Changed across Time, Space, and Altitude

Haag

Jones

Samimi

2019

Climate

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“…Change point detection in time series data were performed with the cpm package using raw time series data. 23 For clarity of presentation, plots in Figure 1 were generated using a 7 day moving average to mitigate the routine effect of app use reductions occurring on weekends (Online Supplement, Figure S1). Country-level reductions in rate of app use were generated by (a) taking the mean daily counts for April 13, 2020 through April 18, 2020; (b) taking the mean daily counts of app use from Sep 1, 2020 through Nov 1, 2020; and then calculating (a)/(b), yielding the app use for the most recent data available as a percent of baseline use.…”

Section: Methodsmentioning

confidence: 99%

Real-time assessment of COVID-19 impact on global surgical case volumes

O’Reilly-Shah

Cleve

Long

et al. 2020

Preprint

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Importance: The COVID-19 pandemic has disrupted global surgical capacity. The impact of the pandemic in low and middle income countries has the potential to worsen already strained access to surgical care. Timely assessment of surgical volumes in these countries remains challenging. Objective:To determine whether usage data from a globally used anesthesiology calculator mobile application can serve as a proxy for global surgical case volume and contribute to monitoring of the impact of the COVID-19 pandemic, particularly in World Bank low income countries where official data collection is not currently practical.Design: Subset of data from an ongoing observational cohort study of users of the application collected from Setting: The mobile application is available from public sources; users download and use the application per their own clinical needs on personal mobile devices. Participants:No user data was excluded from the study. Exposure(s):Events with impacts on surgical case volumes, including weekends, holidays, and the COVID-19 pandemic. Main Outcome(s) and Measure(s):It was previously noted that application usage was decreased on weekends and during winter holidays. We subsequently hypothesized that more detailed analysis would reveal impacts of country-specific or region-specific holidays on the volume of app use.Results: 4,300,975 data points from 92,878 unique users were analyzed. Physicians and other anesthesia providers comprised 85.8% of the study population. Application use was reduced on holidays and weekends and correlated with fluctuations in surgical volume. The COVID-19 pandemic was associated with substantial reductions in app use globally and regionally. There was strong cross correlation between COVID-19 case count and reductions in app use. By country, there was a median global reduction in app use to 58% of baseline (interquartile range, 46%-75%). Application use in low-income continues to decline but in high-income countries has stabilized. Conclusions and Relevance:Application usage metadata provides a real-time indicator of surgical volume. This data may be used to identify impacted regions where disruptions to surgical care are disproportionate or prolonged. A dashboard for continuous visualization of these data has been deployed.

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“…The roughness of the surfaces was determined using a PHP script of the authors, while the surfaces were digitally mapped with AutoCAD 2016. The breakpoint detection was performed in R statistical environment (R Core Team 2018) using the breakpoint package in the case of the CEM (Priyadarshana and Sofronov 2015), while in the case of the CPM (Ross 2015), the cpm package. The Cullen-Frey diagrams were plotted using the descdist() function of the fitdistrplus package (Delignette-Muller and Dutang 2015).…”

Section: Software Usedmentioning

confidence: 99%

Shear strength testing of consolidated claystones: breakpoint detection of shear stress versus shear displacement curves, a statistical approach

Rozgonyi-Boissinot

Buocz²,

Hatvani

et al. 2021

Int J Geomath

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The evaluation of shear stress versus shear displacement curves is in the main focus of geotechnical engineering. Such curves, depending on the rock assessed, consist of a quasi-linear section, followed by a “kick” representing the peak shear strength, and a residual part, mostly parallel to the abscissa. The aim of the present study is to facilitate the future automatic detection of these crucial characteristics to take a step towards replacing their visual/analogue determination via modern statistical tools. Breakpoint detection methods (Cross-Entropy, Change Point Model) were applied to curves obtained from laboratory shear tests describing the shearing along discontinuities of nine Mont Terri Opalinus Claystone samples. Smooth and moderately rough claystone surfaces were studied. Results indicated that the end of the rising section and the kick observed on the shear strength curves was effectively approximated with the Change Point Model framework. An additional practical advantage of applying statistical tools such as breakpoint detection to shear strength determination is that it ensures the comparability of the obtained results.

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Parametric and Nonparametric Sequential Change Detection in R: The cpm Package

Cited by 152 publications

References 34 publications

Central Asia’s Changing Climate: How Temperature and Precipitation Have Changed across Time, Space, and Altitude

Central Asia’s Changing Climate: How Temperature and Precipitation Have Changed across Time, Space, and Altitude

Real-time assessment of COVID-19 impact on global surgical case volumes

Shear strength testing of consolidated claystones: breakpoint detection of shear stress versus shear displacement curves, a statistical approach

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