postSij: Compute random draw from full conditional posterior for s_ij...
In skipTrack: A Bayesian Hierarchical Model that Controls for Non-Adherence in Mobile Menstrual Cycle Tracking
postSij R Documentation
Compute random draw from full conditional posterior for s_ij in Li algorithm.
Description
This function calculates a random draw from the full conditional posterior distribution
for s_ij in the Li algorithm, given the observed values yijs, the parameter pi,
the lambda_i value, and the truncation level S.
Usage
postSij(yijs, pii, lambdai, S)
Arguments
yijs
Vector of observed values for s_ij.
pii
Probability parameter pi.
lambdai
Value of lambda_i.
S
Truncation level.
Value
A random draw from the posterior distribution of s_ij.
skipTrack documentation built on April 3, 2025, 6:21 p.m.
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| postSij | R Documentation |
Compute random draw from full conditional posterior for s_ij in Li algorithm.
Description
This function calculates a random draw from the full conditional posterior distribution for s_ij in the Li algorithm, given the observed values yijs, the parameter pi, the lambda_i value, and the truncation level S.
Usage
postSij(yijs, pii, lambdai, S)
Arguments
yijs |
Vector of observed values for s_ij. |
pii |
Probability parameter pi. |
lambdai |
Value of lambda_i. |
S |
Truncation level. |
Value
A random draw from the posterior distribution of s_ij.
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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