Adds block structure to a GP object, allowing simulating and sampling (in an MCMC setup) from blocks of coefficients, as opposed to all the coefficients at once. The size of the blocks will usually increase with increasing frequency as the most important coefficients are those for the low frequency basis functions.

1 2 | ```
## S3 method for class 'gp'
add.blocks(object, breaks = NULL,...)
``` |

`object` |
A GP object, created by |

`breaks` |
An optional vector of increasing frequency values that allow for binning the coefficients based on the frequencies of the basis functions with which they are associated. The maximum value of the vector should be one half the number of gridpoints in the dimension with the largest number of gridpoints (e.g., 64, if gridsize=c(32,128)). |

`...` |
Other arguments. |

The function sets up a block structure with blocks with increasing
numbers of coefficients as the frequencies increase. The frequency
in question is the highest frequency of the (*omega_1,omega_2*) pair in
the two-dimensional situation. E.g., the default block structure is
c(1,2,4,8,16,...), which means that the first block is the
coefficients whose maximum frequency is 1, the second with maximum
frequency is 2, the third with maximum frequency of 3 and 4, the
fourth with maximum frequency between 5 and 8, etc.

The function modifies the GP object, which is essentially a pointer (an R environment in this case), so NULL is returned.

Christopher Paciorek paciorek@alumni.cmu.edu

Type 'citation("spectralGP")' for references.

1 2 3 4 5 6 7 8 9 | ```
library(spectralGP)
gp1=gp(128,matern.specdens,c(1,4))
gp2=gp(c(64,64),matern.specdens,c(1,4))
add.blocks(gp1,c(1,3,7,15,31,64))
add.blocks(gp2)
propose.coeff(gp1,block=5)
plot(gp1)
propose.coeff(gp2,block=2,proposal.sd=0.1)
plot(gp2)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.