demo_simple_gaussian: Tests 1-dimensional Gaussian Distribution with customized...
In KSD: Goodness-of-Fit Tests using Kernelized Stein Discrepancy
View source: R/demo_simple_gmm.R
Description
We generate a gaussian distribution with given parameters,
and add noise to this dataset. We then compute the score
of each dataset for the original true distribution.
Usage
1
demo_simple_gaussian(truemu = 5, truesd = 1, noisemu = 0, noisesd = 2, n = 100)
Arguments
truemu
mean of true distribution
truesd
standard deviation of true distribution
noisemu
mean of gaussian noise to add
noisesd
standard deviation of gaussian noise to add
n
number of samples to generate
KSD documentation built on Jan. 13, 2021, 8:39 a.m.
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View source: R/demo_simple_gmm.R
Description
We generate a gaussian distribution with given parameters, and add noise to this dataset. We then compute the score of each dataset for the original true distribution.
Usage
1 | demo_simple_gaussian(truemu = 5, truesd = 1, noisemu = 0, noisesd = 2, n = 100)
|
Arguments
truemu |
mean of true distribution |
truesd |
standard deviation of true distribution |
noisemu |
mean of gaussian noise to add |
noisesd |
standard deviation of gaussian noise to add |
n |
number of samples to generate |
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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