View source: R/bayesianSplineFit.R
Simulation and model options for the natural b-spline model
1 2 3 4 5 6 7 8 9 10 11 12 | bayes.splines.model.options(iterations = 10000, burnin = 500,
thin = 1, print = 1, knots.prob.birth = 0.5, knots.min = 1,
knots.max = NA, knots.stepSize = 3, knots.positions.start = NULL,
knots.positions.candidate = NULL, prob.min = 1e-05,
prob.max = 0.99999, accept.rate.adjust = 1,
dropout.estimationTimes = NULL, sigma.beta = NULL,
sigma.residual = NULL, sigma.error = NULL,
sigma.error.shape.tau = NULL, sigma.error.rate.tau = NULL,
lambda.numKnots = NULL, sigma.randomIntercept = NULL,
sigma.randomSlope = NULL, sigma.randomInterceptSlope = NULL,
sigma.randomEffects.df = NULL, sigma.randomEffects.scale = NULL,
eta.null = NULL)
|
iterations |
number of iterations for the MCMC simulation |
burnin |
burn in period for the simulation, i.e. the number of iterations to throw away at the beginning of the simulation |
thin |
thinning interval, i.e. if thin=n, only keep every nth iteration |
knots.prob.birth |
probability of adding a new knot to the model on a given iteration |
knots.min |
minimum number of knots in the model. Must be greater than or equal to 1. |
knots.max |
maximum number of knots in the model. |
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