multinomial_resampling: Multinomial resampling (fast implementation)
In pierrejacob/PET:
Description
Usage
Arguments
Details
Value
Examples
Description
Sample nsamples times from a categorical
distribution with probabilities given by normalized_weights.
Usage
1
multinomial_resampling(nsamples, normalized_weights)
Arguments
nsamples
is a number of desired samples
normalized_weights
is a vector of probabilities (non-negative values summing to one)
Details
This implementation is in C++, based on drawing sorted uniforms.
Value
a vector of nsamples integers between 1 and the size of normalized_weights.
Examples
1
2
3
4
5
N <- 1000
logweights <- rnorm(N)
normalize_weight_results <- normalize_weight(logweights)
normalized_weights <- normalize_weight_results$nw
multinomial_resampling(10, normalized_weights)
pierrejacob/PET documentation built on May 25, 2019, 11:35 p.m.
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Description Usage Arguments Details Value Examples
Description
Sample nsamples times from a categorical
distribution with probabilities given by normalized_weights.
Usage
1 | multinomial_resampling(nsamples, normalized_weights)
|
Arguments
nsamples |
is a number of desired samples |
normalized_weights |
is a vector of probabilities (non-negative values summing to one) |
Details
This implementation is in C++, based on drawing sorted uniforms.
Value
a vector of nsamples integers between 1 and the size of normalized_weights.
Examples
1 2 3 4 5 | N <- 1000
logweights <- rnorm(N)
normalize_weight_results <- normalize_weight(logweights)
normalized_weights <- normalize_weight_results$nw
multinomial_resampling(10, normalized_weights)
|
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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