Rev Language Reference
mvMirror
The adaptive mirror (normal) proposal of Thawornwattana et al. 2017, uses MCMC samples to find posterior mean and variance. After user-defined waiting time, proposes moves on opposite side of posterior mean from current location using a normal distribution with the learned posterior standard deviation (scaled by lambda). Before this time, the move uses mu0 as the mean, and lambda as the standard deviation. WARNING: Disabling tuning disables both tuning of proposal variance and learning of empirical mean and variance. To learn the empirical mean and variance without tuning sigma, set adaptOnly=true.
Usage
mvMirror(Real x, Natural waitBeforeLearning, Natural waitBeforeUsing, Natural maxUpdates, Real mu0, RealPos sigma, Bool tune, Bool adaptOnly, RealPos weight, Probability tuneTarget)
Arguments
| x : | Real (<stochastic> pass by reference) |
| The variable on which this move operates. | |
| waitBeforeLearning : | Natural (pass by value) |
| The number of move attempts to wait before tracking the mean and variance of the variable. | |
| Default : 500 | |
| waitBeforeUsing : | Natural (pass by value) |
| The number of move attempts to wait before using the learned mean and variance. | |
| Default : 1000 | |
| maxUpdates : | Natural (pass by value) |
| The maximum number of updates to the empirical mean and variance. | |
| Default : 10000 | |
| mu0 : | Real (pass by value) |
| Initial guess at posterior mean. | |
| Default : 0 | |
| sigma : | RealPos (pass by value) |
| The tuning parameter, adjusts variance of proposal. | |
| Default : 1 | |
| tune : | Bool (pass by value) |
| Should we tune the move during burnin? | |
| Default : TRUE | |
| adaptOnly : | Bool (pass by value) |
| If true, sigma is not tuned but mean and variance are still learned | |
| Default : FALSE | |
| weight : | RealPos (pass by value) |
| The weight determines the relative frequency with which this move will be attempted. For details, see the description of the 'moveschedule' parameter on the documentation page for 'mcmc()'. | |
| Default : 1 | |
| tuneTarget : | Probability (pass by value) |
| The acceptance probability targeted by auto-tuning. | |
| Default : 0.44 |
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