In admixture such that the probability density function (pdf) follows l = p*f + (1-p)*g, where p is the unknown weight and f is the unknown component distribution: transforms g of the two-component mixture ditribution to a Uniform distribution. Useful to use Patra and Sen estimator for the estimation of the unknown weight p.
knownComp_to_uniform(data, comp.dist, comp.param)
Observations of the sample under study, following an admixture distribution.
A list with two elements corresponding to component distributions (specified with R native names for these distributions) involved in the admixture model. Unknown elements must be specified as 'NULL' objects, e.g. when 'f' is unknown: list(f=NULL, g='norm').
A list with two elements corresponding to the parameters of the component distributions, each element being a list itself. The names used in this list must correspond to the native R argument names for these distributions. Unknown elements must be specified as 'NULL' objects, e.g. if 'f' is unknown: list(f=NULL, g=list(mean=0,sd=1)).
The transformed data, i.e. the transformed mixture distribution where the known component g now follows a Uniform(0,1) distribution.
Xavier Milhaud firstname.lastname@example.org
## Simulate data: list.comp <- list(f1 = 'norm', g1 = 'norm') list.param <- list(f1 = list(mean = 3, sd = 0.5), g1 = list(mean = 0, sd = 1)) sample1 <- rsimmix(n=1500, unknownComp_weight=0.5, comp.dist = list(list.comp$f1,list.comp$g1), comp.param=list(list.param$f1,list.param$g1)) plot_admix(sim.X = sample1[['mixt.data']], support = 'continuous')## Transform the known component into a Uniform(0,1) distribution: list.comp <- list(f1 = NULL, g1 = 'norm') list.param <- list(f1 = NULL, g1 = list(mean = 0, sd = 1)) transformed_data <- knownComp_to_uniform(data = sample1[['mixt.data']], comp.dist = list.comp, comp.param = list.param) plot_admix(sim.X = transformed_data, support = 'continuous')