rsamplers.rsampler.sample is the function that runs the sampling for different chains on an rsamplers.rsampler object to get a sample.

The syntax is

results = sample(obj,varargin)

Args:

• obj is a member of one of the following classes:

  • rsamplers.rwmh : Random-Walk Metropolis-Hastings

  • rsamplers.imh : Independent Metropolis-Hastings

  • rsamplers.apt : Adaptive parallel tempering

  • rsamplers.slice : slice sampler

  • rsamplers.usrsmplr : user-defined sampler

• *varargin* are class-specific extra arguments

Hint

After sampling, RISE has functions for thinning, burnin, etc. through subsetting. See e.g. help on mdd (constructor for marginal data density objects).

Warning

please check the sign of the target function and make sure the algorithm used conforms with that sign. Of course, changing the sign of the target function is easy

newtarget=@(varargin)-target(varargin{:})

Hint

For your convenience, some shortcuts are available so that you do not have to first create an object and then do the sampling. Moreover you do not have to create a new target if the problem is already a minimization problem. Those shortcuts are : sampler_rwmh, sampler_imh, sampler_apt, sampler_slice. They can be called using one of the following syntaxes (for the details for the inputs, see the base functions):

• results = sampler_XXXX(target,x0,lb,ub)

• results = sampler_XXXX(target,x0,lb,ub,opts)