Description Usage Arguments Value Author(s) See Also Examples
A set of resampling functions with unbiased number of replicates.
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weights |
a vector of weights, possibly logged, unnormalized, or both |
num.samples |
a scalar indicating the number of samples to return (for ‘branching.resample’, ‘num.samples’ is the expected number of samples as the actual number is random) |
method |
a character string indicating the resampling method to use. One of ‘"multinomial"’ (default), ‘"residual"’, ‘"stratified"’, ‘"systematic"’, or ‘"branching"’, can be abbreviated. |
nonuniformity |
a character string indicating which hueristic to use for measuring weight nonuniformity. One of ‘"none"’ (default), ‘"ess"’, ‘"cov"’, or ‘"entropy"’, can be abbreviated. If "none", resampling will always be performed. |
threshold |
a scalar in [0,1] indicating when to resample. If ‘nonuniformity="none"’, resampling is always performed regardless of threshold. If ‘nonuniformity="ess"’ or "entropy", resampling is performed when ‘nonuniformity/num.samples<threshold’. If ‘nonuniformity="cov"’, resampling is performed when 'nonuniformity/log2(num.samples)> threshold'. |
rrf |
for residual resampling, the resampling function to use on the residual |
engine |
run using "R" or "C" code |
log |
if TRUE, the weights are assumed to be logged |
normalized |
if TRUE, the weights are assumed to be normalized and no error checking is done |
weights |
the component weights |
indices |
an integer vector containing the indices of resampled components. If no resampling was performed, then ‘indices=1:length(weights)’. |
Jarad Niemi
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