MC_neff_theoretical: Compute the theoretical effective sample size in two-state...
In maxbiostat/BinaryMarkovChains: Utilities for Two-State Discrete-Time Markov Chains
MC_neff_theoretical R Documentation
Compute the theoretical effective sample size in two-state Markov chain.
Description
This is the theoretical effective sample size for a sample of size N given parameters alpha and p.
Usage
MC_neff_theoretical(N, alpha, p)
Arguments
N
number of iterations
alpha
a transition probability (between 0 and 1)
p
(marginal) success probability
Value
effective sample size
See Also
MC_neff
Examples
p <- .25
MC_neff_theoretical(N = 100, alpha = p, p = p) ## independent sampling gives N_eff = N
maxbiostat/BinaryMarkovChains documentation built on Dec. 11, 2023, 4:29 a.m.
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| MC_neff_theoretical | R Documentation |
Compute the theoretical effective sample size in two-state Markov chain.
Description
This is the theoretical effective sample size for a sample of size N given parameters alpha and p.
Usage
MC_neff_theoretical(N, alpha, p)
Arguments
N |
number of iterations |
alpha |
a transition probability (between 0 and 1) |
p |
(marginal) success probability |
Value
effective sample size
See Also
MC_neff
Examples
p <- .25
MC_neff_theoretical(N = 100, alpha = p, p = p) ## independent sampling gives N_eff = N
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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