detect_peak_modz: Alternative implementation of the robust peak detection...
In animaltracker: Animal Tracker
Description
Usage
Arguments
Value
View source: R/data_analysis.R
Description
Alternative implementation of the robust peak detection algorithm by van Brakel 2014
Classifies data points with modified z-scores greater than max_score as outliers ccording to Iglewicz and Hoaglin 1993
Usage
1
detect_peak_modz(df_comparison, lag = 5, max_score = 3.5)
Arguments
df_comparison
output of compare_flags
lag
width of interval to compute rolling median and MAD, defaults to 5
max_score
modified z-score cutoff to classify observations as outliers, defaults to 3.5
Value
df with classifications
animaltracker documentation built on Nov. 18, 2020, 1:08 a.m.
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Description Usage Arguments Value
View source: R/data_analysis.R
Description
Alternative implementation of the robust peak detection algorithm by van Brakel 2014 Classifies data points with modified z-scores greater than max_score as outliers ccording to Iglewicz and Hoaglin 1993
Usage
1 | detect_peak_modz(df_comparison, lag = 5, max_score = 3.5)
|
Arguments
df_comparison |
output of compare_flags |
lag |
width of interval to compute rolling median and MAD, defaults to 5 |
max_score |
modified z-score cutoff to classify observations as outliers, defaults to 3.5 |
Value
df with classifications
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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