pi_ij_RACS: Calculate joint inclusion probability of unit $j$ and $h$,...
In ksauby/ACS: Adaptive Cluster Sampling
pi_ij_RACS R Documentation
Calculate joint inclusion probability of unit $j$ and $h$, using the RACS correction
Description
Calculate joint inclusion probability of unit $j$ and $h$, using the RACS correction
Usage
pi_ij_RACS(N, n1, m_vec, m_threshold)
Arguments
N
Population size.
n1
An integer giving the initial sample size (e.g., a simple random sample).
m_vec
Vector of values m for the set of units in a sample, of length n1. Each m value within the vector m_vec denotes the number of units satisfying the ACS criterion for the network i to which the unit belongs.
m_threshold
threshold value above which to calculate pi_i and pi_j differently.
References
\insertRefsaubyadaptiveACSampling
ksauby/ACS documentation built on Aug. 18, 2022, 3:33 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.
| pi_ij_RACS | R Documentation |
Calculate joint inclusion probability of unit $j$ and $h$, using the RACS correction
Description
Calculate joint inclusion probability of unit $j$ and $h$, using the RACS correction
Usage
pi_ij_RACS(N, n1, m_vec, m_threshold)
Arguments
N |
Population size. |
n1 |
An integer giving the initial sample size (e.g., a simple random sample). |
m_vec |
Vector of values m for the set of units in a sample, of length n1. Each m value within the vector |
m_threshold |
threshold value above which to calculate pi_i and pi_j differently. |
References
\insertRefsaubyadaptiveACSampling
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.