Use the Bca bootstrap method and the t-boostrap method from the bcaboot and boot packages to generate consonance distrbutions.
curve_boot(data = data, func = func, method = "bca", t0, tt, bb, replicates = 2000, steps = 1000, table = TRUE)
Dataset that is being used to create a consonance function.
Custom function that is used to create parameters of interest that will be bootstrapped.
The boostrap method that will be used to generate the functions. Methods include "bca" which is the default, "bcapar", which is parametric bootstrapping using the bca method and "t", for the t-bootstrap/percentile method.
Only used for the "bcapar" method. Observed estimate of theta, usually by maximum likelihood.
Only used for the "bcapar" method. A vector of parametric bootstrap replications of theta of length B, usually large, say B = 2000
Only used for the "bcapar" method. A B by p matrix of natural sufficient vectors, where p is the dimension of the exponential family.
Indicates how many bootstrap replicates are to be performed. The defaultis currently 20000 but more may be desirable, especially to make the functions more smooth.
Indicates how many consonance intervals are to be calculated at various levels. For example, setting this to 100 will produce 100 consonance intervals from 0 to 100. Setting this to 10000 will produce more consonance levels. By default, it is set to 1000. Increasing the number substantially is not recommended as it will take longer to produce all the intervals and store them into a dataframe.
Indicates whether or not a table output with some relevant statistics should be generated. The default is TRUE and generates a table which is included in the list object.
A list with 7 items where the dataframe of standard values is in the first list and the table for it in the second if table = TRUE. The Bca intervals and table are found in the third and fourth list. The values for the density function are in the fifth object, while the Bca stats are in the sixth and seventh objects.