bal_sample_ordered: Balanced sampling with reordering
In robertsy/assimilr: Local Ensemble Kalman Particle Filters
Description
Usage
Arguments
Value
Description
Same as bal.sample but permute indices to reduce
the number of discontinuities in local resampling.
Draw a balanced sample of size n from 1,...,n with
probabilities w such that agreement with 1:n is maximal
Multiplicities N_1, ..., N_n, i.e. element j is sampled N_j times.
index = numbers of sampled elements
Author: Hans-Rudolf Kuensch
Usage
1
bal_sample_ordered(w, unif = runif(1))
Arguments
w
= probabilities (must sum to one !)
unif
= uniform (pass if deterministic behaviour wished)
Value
list(N, index)
robertsy/assimilr documentation built on May 27, 2019, 10:33 a.m.
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.
Description Usage Arguments Value
Description
Same as bal.sample but permute indices to reduce the number of discontinuities in local resampling.
Draw a balanced sample of size n from 1,...,n with probabilities w such that agreement with 1:n is maximal
Multiplicities N_1, ..., N_n, i.e. element j is sampled N_j times. index = numbers of sampled elements
Author: Hans-Rudolf Kuensch
Usage
1 | bal_sample_ordered(w, unif = runif(1))
|
Arguments
w |
= probabilities (must sum to one !) |
unif |
= uniform (pass if deterministic behaviour wished) |
Value
list(N, index)
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.