effectiveSampleSize: Compute the effective sample size (ESS) of the particles.
In serrsBayes: Bayesian Modelling of Raman Spectroscopy
effectiveSampleSize R Documentation
Compute the effective sample size (ESS) of the particles.
Description
The ESS is a "rule of thumb" for assessing the degeneracy of
the importance distribution:
ESS = \frac{(\sum_{q=1}^Q w_q)^2}{\sum_{q=1}^Q w_q^2}
Usage
effectiveSampleSize(log_weights)
Arguments
log_weights
logarithms of the importance weights of each particle.
Value
the effective sample size, a scalar between 0 and Q
References
Liu, JS (2001) "Monte Carlo Strategies in Scientific Computing." Springer, NY, pp. 34–36.
Examples
x <- runif(100)
effectiveSampleSize(log(x))
serrsBayes documentation built on Oct. 21, 2026, 5:14 p.m.
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| effectiveSampleSize | R Documentation |
Compute the effective sample size (ESS) of the particles.
Description
The ESS is a "rule of thumb" for assessing the degeneracy of the importance distribution:
ESS = \frac{(\sum_{q=1}^Q w_q)^2}{\sum_{q=1}^Q w_q^2}
Usage
effectiveSampleSize(log_weights)
Arguments
log_weights |
logarithms of the importance weights of each particle. |
Value
the effective sample size, a scalar between 0 and Q
References
Liu, JS (2001) "Monte Carlo Strategies in Scientific Computing." Springer, NY, pp. 34–36.
Examples
x <- runif(100)
effectiveSampleSize(log(x))
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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