survBootOutliers

Concordance Based Bootstrap Methods for Outlier Detection in Survival Analysis

CRAN Package

Three new methods to perform outlier detection in a survival context. In total there are six methods provided, the first three methods are traditional residual-based outlier detection methods, the second three are the concordance-based. Package developed during the work on the two following publications: doi:10.5220/0005225300750082; doi:10.1007/978-3-319-27926-8_22.

  • Version1.0
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release05/28/2018

Documentation


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Insights

Last 30 days

This package has been downloaded 105 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.

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9 downloadsFeb 16, 2025
3 downloadsFeb 17, 2025
2 downloadsFeb 18, 2025
4 downloadsFeb 19, 2025
3 downloadsFeb 20, 2025
8 downloadsFeb 21, 2025
1 downloadsFeb 22, 2025
6 downloadsFeb 23, 2025
2 downloadsFeb 24, 2025
1 downloadsFeb 25, 2025
1 downloadsFeb 26, 2025
3 downloadsFeb 27, 2025
2 downloadsFeb 28, 2025
3 downloadsMar 1, 2025
8 downloadsMar 2, 2025
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3 downloadsMar 5, 2025
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1 downloadsMar 8, 2025
0 downloadsMar 9, 2025
3 downloadsMar 10, 2025
7 downloadsMar 11, 2025
2 downloadsMar 12, 2025
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3 downloadsMar 15, 2025
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6 downloadsMar 17, 2025
0 downloadsMar 18, 2025
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0 downloadsMar 21, 2025
0 downloadsMar 22, 2025
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The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 1,524 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 24 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


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Dependencies

  • Depends1 package