Description Usage Arguments Value
View source: R/bayesianSplineFit.R
Add a new knot and use a Metropolis-Hastings step to determine if we keep the changes to the model
1 2 3 | addKnot.gaussian(model.options, knots.previous, knots.positions.candidate,
outcomes, times.dropout, times.observation, covariates, X.previous,
Theta.previous, Z, alpha, betaCovariates, sigma.error)
|
model.options |
model options |
knots.previous |
previous set of knots |
outcomes |
vector of outcomes |
times.dropout |
vector of dropout times |
times.observation |
vector of observation times |
covariates |
data frame of covariates |
X.previous |
previous X matrix |
Theta.previous |
previous Theta values |
Z |
random effects design matrix |
alpha |
random effects |
betaCovariates |
regression coefficients for covariates |
sigma.error |
residual variance |
list containing updated X, knots, Theta, and boolean indicating if change accepted
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