R/nhpp_hmc.R
nhpp_hmc.Rd
fits an exponential linear regression model with log link.
nhpp_hmc(formula, data, warm_up, iter_max, seed = NULL)
formula | formula specifying the design matrix and outcome
akin to |
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data | data.frame from which to extract outcome and covariates |
warm_up | number of iterations in which to tune HMC step-size, these will be discarded |
iter_max | total number of samples for which to run sampler |
seed | random number generator intializing seed |
Fits an exponential linear regression model using a log link via No-U-Turn Sampler (see reference). This model has a \(N(0,\sigma=3)\) prior on all regression coefficients.
No U-Turn Sampler Hoffman, M. and Gelman A.(2014). The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Journal of Machine Learning Research 15 (1593-1623).