rtnorm: Testing truncated Normal sampling
In BART: Bayesian Additive Regression Trees
rtnorm R Documentation
Testing truncated Normal sampling
Description
Truncated Normal latents are necessary to transform a
binary BART into a continuous BART.
Usage
rtnorm(n, mean, sd, tau)
Arguments
n
Number of samples.
mean
Mean.
sd
Standard deviation.
tau
Truncation point.
Value
Returns n truncated Normals, i.e., N(mean, sd)I(tau, infinity).
References
Robert C. (1995)
Simulation of truncated normal variables.
Statistics and computing, 5(2), 121–125.
See Also
pbart, lbart
Examples
set.seed(12)
rtnorm(1, 0, 1, 3)
rtnorm(1, 0, 1, 3)
BART documentation built on June 22, 2024, 11:33 a.m.
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| rtnorm | R Documentation |
Testing truncated Normal sampling
Description
Truncated Normal latents are necessary to transform a binary BART into a continuous BART.
Usage
rtnorm(n, mean, sd, tau)
Arguments
n |
Number of samples. |
mean |
Mean. |
sd |
Standard deviation. |
tau |
Truncation point. |
Value
Returns n truncated Normals, i.e., N(mean, sd)I(tau, infinity).
References
Robert C. (1995) Simulation of truncated normal variables. Statistics and computing, 5(2), 121–125.
See Also
pbart, lbart
Examples
set.seed(12)
rtnorm(1, 0, 1, 3)
rtnorm(1, 0, 1, 3)
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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