empiricalBF: Empirical Bounding Functions
In HPLB: High-Probability Lower Bounds for the Total Variance Distance
Description
Usage
Arguments
Value
Description
Empirical Bounding Functions
Usage
1
empiricalBF(tv.seq, nsim = 1000, m = 100, n = 100, alpha = 0.05)
Arguments
tv.seq
a vector of total variation values between 0 and 1.
nsim
a numeric value giving the number of repetitions.
m
a numeric value, the number of observations left.
n
a numeric value, the number of observations right.
alpha
a numeric value giving the type-I error level.
Value
a list of empirical bounding functions indexed by the tv.seq (in the respective order).
HPLB documentation built on July 1, 2020, 7:10 p.m.
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Description Usage Arguments Value
Description
Empirical Bounding Functions
Usage
1 | empiricalBF(tv.seq, nsim = 1000, m = 100, n = 100, alpha = 0.05)
|
Arguments
tv.seq |
a vector of total variation values between 0 and 1. |
nsim |
a numeric value giving the number of repetitions. |
m |
a numeric value, the number of observations left. |
n |
a numeric value, the number of observations right. |
alpha |
a numeric value giving the type-I error level. |
Value
a list of empirical bounding functions indexed by the tv.seq (in the respective order).
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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