calculateDiscreteEntropy_Grassberger: calculate entropy of an optionally discrete value (X) using a...
In terminological/tidy-info-stats: Functions for manipulating information statistics
View source: R/tidyDiscreteEntropy.R
calculateDiscreteEntropy_Grassberger R Documentation
calculate entropy of an optionally discrete value (X) using a histogram approach using the following method
Description
P. Grassberger, “Entropy Estimates from Insufficient Samplings,” arXiv [physics.data-an], 29-Jul-2003 [Online]. Available: http://arxiv.org/abs/physics/0307138
Usage
calculateDiscreteEntropy_Grassberger(df, groupVars, countVar = NULL, ...)
Arguments
df
- may be grouped, in which case the grouping is interpreted as different types of discrete variable
groupVars
- the columns of the discrete value quoted by the vars() function (e.g. ggplot facet_wrap)
Details
but with a digamma based function (rather than harmonics) detailed in eqns 31 & 35.
For our purposes we fix l=0 to give the form in eqn 27. The error in this method is supposedly better for undersampled cases (where number of bins similar to number of samples)
Value
a dataframe containing the disctinct values of the groups of df, and for each group an entropy value (H). If df was not grouped this will be a single entry
terminological/tidy-info-stats documentation built on Nov. 19, 2022, 11:23 p.m.
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View source: R/tidyDiscreteEntropy.R
| calculateDiscreteEntropy_Grassberger | R Documentation |
calculate entropy of an optionally discrete value (X) using a histogram approach using the following method
Description
P. Grassberger, “Entropy Estimates from Insufficient Samplings,” arXiv [physics.data-an], 29-Jul-2003 [Online]. Available: http://arxiv.org/abs/physics/0307138
Usage
calculateDiscreteEntropy_Grassberger(df, groupVars, countVar = NULL, ...)
Arguments
df |
- may be grouped, in which case the grouping is interpreted as different types of discrete variable |
groupVars |
- the columns of the discrete value quoted by the vars() function (e.g. ggplot facet_wrap) |
Details
but with a digamma based function (rather than harmonics) detailed in eqns 31 & 35. For our purposes we fix l=0 to give the form in eqn 27. The error in this method is supposedly better for undersampled cases (where number of bins similar to number of samples)
Value
a dataframe containing the disctinct values of the groups of df, and for each group an entropy value (H). If df was not grouped this will be a single entry
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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