RI: Intraclass Correlation Coefficient for layer boundary...
In maxgav13/GMisc: Miscellaneous Functions for Geology (and its areas)
RI R Documentation
Intraclass Correlation Coefficient for layer boundary determination
Description
Calculates the intraclass correlation coefficient (RI) for a perforation log, and shows the locations where this coefficient is higher than 0.7 and 0.8. The coefficient is used to find layer boundaries in a perforation log.
Usage
RI(data, k = 6)
Arguments
data
data A data frame containing the depth in the first column, and the value of interest in the second column
k
The window length for the number of data points to include in the calculation of RI. Always and even (par) number. Larger values make the resulting statistic smoother
Details
The example data given is intended to show the structure needed for input data. The user should follow this structure, which in general corresponds with a data frame with a sequence in the first column and the observed/measured values in the second column
Value
ggplot and plotly objects showing the RI statistic and lines marking the critical values of 0.7 and 0.8, and suggested boundaries
References
Mora, R. (2013). Uso de metodos estadisticos para la determinacion de capas homogeneas de suelos volcanicos en un sitio de las laderas del Volcan Irazu, Cartago, Costa Rica. - Rev. Geol. Amer. Central, 49: 101-108.
Examples
RI(DPM_data, k = 6)
maxgav13/GMisc documentation built on June 12, 2022, 3:48 a.m.
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| RI | R Documentation |
Intraclass Correlation Coefficient for layer boundary determination
Description
Calculates the intraclass correlation coefficient (RI) for a perforation log, and shows the locations where this coefficient is higher than 0.7 and 0.8. The coefficient is used to find layer boundaries in a perforation log.
Usage
RI(data, k = 6)
Arguments
data |
data A data frame containing the depth in the first column, and the value of interest in the second column |
k |
The window length for the number of data points to include in the calculation of RI. Always and even (par) number. Larger values make the resulting statistic smoother |
Details
The example data given is intended to show the structure needed for input data. The user should follow this structure, which in general corresponds with a data frame with a sequence in the first column and the observed/measured values in the second column
Value
ggplot and plotly objects showing the RI statistic and lines marking the critical values of 0.7 and 0.8, and suggested boundaries
References
Mora, R. (2013). Uso de metodos estadisticos para la determinacion de capas homogeneas de suelos volcanicos en un sitio de las laderas del Volcan Irazu, Cartago, Costa Rica. - Rev. Geol. Amer. Central, 49: 101-108.
Examples
RI(DPM_data, k = 6)
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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