Create an admixture model, also known as (aka) a contamination model. Such a model is a two-component mixture model with one known component. Both the second component distribution and the mixing weight are unknown.
Arguments
- knownComp_dist
(Character) The name of the distribution (specified as in R glossary) of the known component of the admixture model
- knownComp_param
(Character) A vector of the names of the parameters (specified as in R glossary) involved in the chosen known distribution, with their values.
Value
An object of class 'admix_model', containing 2 attributes: 1) a list that gives the information about the distributions involved in the two-component mixture model (the unknown and the known ones); 2) a list that gives the information about the corresponding parameters of those distributions.
Author
Xavier Milhaud xavier.milhaud.research@gmail.com
Examples
admix_model(knownComp_dist = "norm", knownComp_param = list("mean"=0, "sd"=1))
#> Call:admix_model(knownComp_dist = "norm", knownComp_param = list(mean = 0,
#> sd = 1))
#>
#> Known component distribution: norm
#> Value of the known component parameters:
#> $mean
#> [1] 0
#>
#> $sd
#> [1] 1
#>
admix_model(knownComp_dist = "exp", knownComp_param = list("rate"=2))
#> Call:admix_model(knownComp_dist = "exp", knownComp_param = list(rate = 2))
#>
#> Known component distribution: exp
#> Value of the known component parameters:
#> $rate
#> [1] 2
#>
admix_model(knownComp_dist = "multinom", knownComp_param = list("size"=1, "prob"=c(0.2,0.8,0.1)))
#> Call:admix_model(knownComp_dist = "multinom", knownComp_param = list(size = 1,
#> prob = c(0.2, 0.8, 0.1)))
#>
#> Known component distribution: multinom
#> Value of the known component parameters:
#> $size
#> [1] 1
#>
#> $prob
#> [1] 0.2 0.8 0.1
#>