Monitoring Data in R with the lumberjack Package

被引:7
|
作者
van der Loo, Mark P. J. [1 ]
机构
[1] Stat Netherlands, Res & Dev, Henri Faasdreef 312, NL-2492 JP The Hague, Netherlands
来源
JOURNAL OF STATISTICAL SOFTWARE | 2021年 / 98卷 / 01期
关键词
data quality; process monitoring; logging; debugging; R;
D O I
10.18637/jss.v098.i01
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Monitoring data while it is processed and transformed can yield detailed insight into the dynamics of a (running) production system. The lumberjack package is a lightweight package allowing users to follow how an R object is transformed as it is manipulated by R code. The package abstracts all logging code from the user, who only needs to specify which objects are logged and what information should be logged. A few default loggers are included with the package but the package is extensible through user-defined logger objects.
引用
收藏
页码:1 / 13
页数:13
相关论文
共 50 条
  • [1] Preparing GIS data for analysis of stream monitoring data: The R package openSTARS
    Kattwinkel, Mira
    Szocs, Eduard
    Peterson, Erin
    Schafer, Ralf B.
    PLOS ONE, 2020, 15 (09):
  • [2] Monitoring ecosystem degradation using spatial data and the R package spatialwarnings
    Genin, Alexandre
    Majumder, Sabiha
    Sankaran, Sumithra
    Danet, Alain
    Guttal, Vishwesha
    Schneider, Florian D.
    Kefi, Sonia
    METHODS IN ECOLOGY AND EVOLUTION, 2018, 9 (10): : 2067 - 2075
  • [3] An R package for correcting continuous water quality monitoring data for drift
    Andrew R. Shaughnessy
    Christopher G. Prener
    Elizabeth A. Hasenmueller
    Environmental Monitoring and Assessment, 2019, 191
  • [4] Update to ttprocessing: the R-package to handle the TreeTalker monitoring data
    Kabala, J. P.
    Niccoli, F.
    Battipaglia, G.
    DENDROCHRONOLOGIA, 2024, 84
  • [5] An R package for correcting continuous water quality monitoring data for drift
    Shaughnessy, Andrew R.
    Prener, Christopher G.
    Hasenmueller, Elizabeth A.
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2019, 191 (07)
  • [6] Introducing the Continuous Glucose Data Analysis (CGDA) R Package: An Intuitive Package to Analyze Continuous Glucose Monitoring Data
    Attaye, Ilias
    van der Vossen, Eduard W. J.
    Mendes Bastos, Diogo N.
    Nieuwdorp, Max
    Levin, Evgeni
    JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, 2022, 16 (03): : 783 - 785
  • [7] RespirAnalyzer: an R package for analyzing data from continuous monitoring of respiratory signals
    Zhang, Teng
    Dong, Xinzheng
    Wang, Dandan
    Huang, Chen
    Zhang, Xiaohua Douglas
    BIOINFORMATICS ADVANCES, 2024, 4 (01):
  • [8] SpTe2M: An R package for nonparametric modeling and monitoring of spatiotemporal data
    Yang, Kai
    Qiu, Peihua
    JOURNAL OF QUALITY TECHNOLOGY, 2023, 56 (02) : 140 - 156
  • [9] CAVIAR: an R package for checking, displaying and processing wood-formation-monitoring data
    Rathgeber, Cyrille B. K.
    Santenoise, Philippe
    Cuny, Henri E.
    TREE PHYSIOLOGY, 2018, 38 (08) : 1246 - 1260
  • [10] Surveillance:: An R package for the monitoring of infectious diseases
    Hoehle, Michael
    COMPUTATIONAL STATISTICS, 2007, 22 (04) : 571 - 582