powered by
Histogram
p
[vector] Vector of probability
c
[matrix] Vector of center of bins, with nrow = n_samples and ncol = n_features
bin_width
[vector or NULL] A vector of lengths of the cells discretizing R^numbers of variables. If NULL, it is estimating during the fit
bin_origin
[vector or NULL] Coordinate of lower corner of one cell. If NULL, c(0,...,0) is used
OTHist$new()
OTHist$clone()
new()
Create a new OTHist object.
OTHist$new(p, c)
A new `OTHist` object.
clone()
The objects of this class are cloneable with this method.
OTHist$clone(deep = FALSE)
deep
Whether to make a deep clone.
Just a generic class which contains two arguments, p (probability) and c (center of bins)
## Build a random discrete probability distribution p = stats::rnorm(100) p = p / base::sum(p) c = base::seq( -1 , 1 , length = 100 ) mu = OTHist$new( p , c )
Run the code above in your browser using DataLab