<b>fitdistrplus</b>: An<i>R</i>Package for Fitting Distributions

Delignette-Muller, Marie Laure; Dutang, Christophe

doi:10.18637/jss.v064.i04

Cited by 1,746 publications

(1,011 citation statements)

References 77 publications

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“…The 'descdist' procedure (from R's fitdistrplus package) was used to identify the distribution using a 'Cullen and Frey' graph for discrete values [24,25] with 100 bootstrap samples. The proposed distribution was examined to model the delays and identify withdrawn contributors.…”

Section: Identifying Withdrawn Contributorsmentioning

confidence: 99%

Contributors’ Withdrawal from Online Collaborative Communities: The Case of OpenStreetMap

Bégin

Devillers

Roche

2017

IJGI

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Online collaborative communities are now ubiquitous. Identifying the nature of the events that drive contributors to withdraw from a project is of prime importance to ensure the sustainability of those communities. Previous studies used ad hoc criteria to identify withdrawn contributors, preventing comparisons between results and introducing interpretation biases. This paper compares different methods to identify withdrawn contributors, proposing a probabilistic approach. Withdrawals from the OpenStreetMap (OSM) community are investigated using time series and survival analyses. Survival analysis revealed that participants' withdrawal pattern compares with the life cycles studied in reliability engineering. For OSM contributors, this life cycle would translate into three phases: "evaluation," "engagement" and "detachment." Time series analysis, when compared with the different events that may have affected the motivation of OSM participants over time, showed that an internal conflict about a license change was related to largest bursts of withdrawals in the history of the OSM project. This paper not only illustrates a formal approach to assess withdrawals from online communities, but also sheds new light on contributors' behavior, their life cycle, and events that may affect the length of their participation in such project.

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Section: Identifying Withdrawn Contributorsmentioning

confidence: 99%

Contributors’ Withdrawal from Online Collaborative Communities: The Case of OpenStreetMap

Bégin

Devillers

Roche

2017

IJGI

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“…These estimation methods are used to determine a probability distribution modeling the random variable, and to find parameter estimation for that distribution (Delignett-Muller & Dutang, 2014).…”

Section: = L(bˆ) − 2 Logmentioning

confidence: 99%

Modeling Time-to-Acceptance for ISI-Indexed Journals in the Profession of Library and Information Science

Yang

2017

IJoL

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Abstract:There are many factors affecting review duration after a paper has been submitted to a journal. Developing a time-to-acceptance model of each journal for the whole time span from submission to acceptance can help researchers when they are selecting journals to publish research results, as well as help editors when they are optimizing workflow and strategy. Using ISI-indexed journals in the profession of library and information science as an example, this study aims to explore the possible patterns of time-to-acceptance for refereed articles. Based on the theories of maximum likelihood estimation, this article models probability distributions for the retrieved data through the R package fitdistrplus. The Kolmogorov-Smirnov test is further used to determine if the distribution for each journal can be accepted. ABSTRACTThere are many factors affecting review duration after a paper has been submitted to a journal. Developing a time-to-acceptance model of each journal for the whole time span from submission to acceptance can help researchers when they are selecting journals to publish research results, as well as help editors when they are optimizing workflow and strategy. Using ISI-indexed journals in the profession of library and information science as an example, this study aims to explore the possible patterns of time-to-acceptance for refereed articles. Based on the theories of maximum likelihood estimation, this article models probability distributions for the retrieved data through the R package fitdistrplus. The Kolmogorov-Smirnov test is further used to determine if the distribution for each journal can be accepted.

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“…The fitted distribution which has the lowest values of parameters AIC and BIC is taken to be optimal, as according to Dziak et al [34]. The fitting was done using the "fitdistrplus" package [35], which is a part of the R software [27]. The fitted distribution is associated with the allocation of the corresponding subpopulation in the area.…”

Section: Generating Virtual Standmentioning

confidence: 99%

Generating Virtual Even-Aged Silver Fir Stand Structure Based on the Measured Sample Plots

Beljan

Vedriš

Mikac

et al. 2016

SEEFOR

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fitdistrplus: AnRPackage for Fitting Distributions

Cited by 1,746 publications

References 77 publications

Contributors’ Withdrawal from Online Collaborative Communities: The Case of OpenStreetMap

Contributors’ Withdrawal from Online Collaborative Communities: The Case of OpenStreetMap

Modeling Time-to-Acceptance for ISI-Indexed Journals in the Profession of Library and Information Science

Generating Virtual Even-Aged Silver Fir Stand Structure Based on the Measured Sample Plots

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