resample_snps: Run models while leaving out SNP blocks

In uqrmaie1/admixtools: Inferring demographic history from genetic data

Run models while leaving out SNP blocks

Description

These are wrapper functions around various qp functions, which will evaluate a model on multiple subdivisions of the data. The subdivisions are formed by leaving out one or more SNP block at a time (see boot for details).

Usage

qp3pop_resample_snps(f2_blocks, boot = FALSE, ...)

qpdstat_resample_snps(f2_blocks, boot = FALSE, ...)

qpwave_resample_snps(f2_blocks, boot = FALSE, ...)

qpadm_resample_snps(f2_blocks, boot = FALSE, ...)

qpgraph_resample_snps(f2_blocks, boot = FALSE, ...)

Arguments

f2_blocks	a 3d array of blocked f2 statistics
boot	If FALSE (the default), block-jackknife resampling will be used to compute standard errors. Otherwise, block-bootstrap resampling will be used to compute standard errors. If boot is an integer, that number will specify the number of bootstrap resamplings. If boot = TRUE, the number of bootstrap resamplings will be equal to the number of SNP blocks.
...	named arguments which are passed to the qp function.
verbose	print progress updates

Value

a nested data frame where each model is a row, and the columns are model parameters and model outputs

Examples

## Not run: 
res = qpadm_resample_snps(example_f2_blocks, target = target, left = left, right = right)
unnest(res, weights)

## End(Not run)

uqrmaie1/admixtools documentation built on Nov. 3, 2024, 12:56 a.m.