NEWS

impala 0.1.4.9000

add fixTheta()/unfixTheta() to hold calibration parameters at fixed values, supporting conditional and cut-Bayes inference
document that sd_est, s2_df and s2_ind in addVecExperiments() are indexed by measurement error group, so a separate standard deviation can be learned per group -- including one per component of yobs via s2_ind = seq_along(yobs)
addVecExperiments() now validates sd_est, s2_df and s2_ind instead of silently dropping observations or corrupting the error prior; 0-based s2_ind (as used by python impala) is rejected with a message rather than leaving an empty group
add optional sd_lower/sd_upper bounds on the learned measurement error standard deviations, enforced in both the Gibbs and Metropolis-Hastings s2 updates
fix calibPool() failing with "incorrect number of dimensions" for emulator models at a single temperature
add ability to specify priors for theta (#8)
cleaned up documentation
numerical bugfixes
added test harness (#11)