sample_drop_model {simDNAmixtures} | R Documentation |
Sample drop model(s) with parameters according to priors
Description
Sample drop model(s) with parameters according to priors
Usage
sample_drop_model(
number_of_contributors,
sampling_parameters,
drop_in_rate = 0,
model_settings
)
Arguments
number_of_contributors |
Integer |
sampling_parameters |
List. Needs to contain:
|
drop_in_rate |
Numeric vector of length one. Expected number of drop-ins per locus. Default is 0. |
model_settings |
List. See drop_model. |
Details
In simulation studies involving many mixed DNA profiles, one often needs to generate various samples with different model parameters. This function samples a drop model with parameters according to prior distributions. The dropout probability for each contributor is sampled uniformly between min_dropout_probability.
and max_dropout_probability
.
Value
When length(number_of_contributors)==1
, a single drop_model of class pg_model
. Otherwise, a list of these.
See Also
sample_mixtures_fixed_parameters to directly supply parameters of choice for more control
Examples
gf <- gf_configuration()
sampling_parameters <- list(min_dropout_probability. = 0., max_dropout_probability. = 0.5)
model <- sample_drop_model(number_of_contributors = 1,
sampling_parameters = sampling_parameters,
model_settings = list(locus_names = gf$autosomal_markers,
size_regression = gf$size_regression))