fit_nngp: Fit the nearest-neighbor Gaussian process.
In hillarykoch/locdiffr: analysis of LOCal DIFFerences in chromatin aRchitecture

Run the MCMC to fit the nearest-neighbor Gaussian process for a collection of window sizes.

1	fit_nngp(infile, outpath, num_neighbors = 1, iters = 15000, parallel = FALSE, ncores = 10, return = FALSE)

`infile`	Path to the rds file output by run_scc_scan
`outpath`	Path to where the output will be written. The output file should be given the .rds file extension.
`num_neighbors`	Integer number of nearest neighbors to use. Defaults to 1.
`iters`	Number of MCMC iterations to use. Defaults to 15,000
`parallel`	Logical. Should the MCMC fitting be parallelized?
`ncores`	If parallel = TRUE, number of cores to parallelize over.
`return`	Logical. Should the output also be returned by the function?

This function fits the nearest-neighbor Gaussian process for the window sizes used in the SCC scan associated with the infile.

If return = TRUE, this function outputs a list of posterior samples across the window sizes contained in the infile.

1 2	# Fit the nearest-neighbor Gaussian process model via MCMC fit_nngp(infile = "inst/extdata/output/z.rds", outpath = "inst/extdata/output/fit.rds", num_neighbors = 1, iters = 150, parallel = FALSE)