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Do not model a limit of detection

Source: R/model_measurements.R
LOD_none.Rd

This option drops all zero measurements from the likelihood and does not explicitly model a limit of detection.

Usage

LOD_none(modeldata = modeldata_init())

Arguments

modeldata

A modeldata object to which the above model specifications should be added. Default is an empty model given by modeldata_init(). Can also be an already partly specified model returned by other EpiSewer modeling functions.

Value

A modeldata object containing data and specifications of the model to be fitted. Can be passed on to other EpiSewer modeling functions to add further data and model specifications.

The modeldata object also includes information about parameter initialization (init), meta data (.metainfo), and checks to be performed before model fitting (.checks).

Details

Dropping zero measurements implicitly assumes that any level of concentration can theoretically lead to a zero measurement. Since the corresponding observations are dropped, this will discard information, but not bias estimates.

See also

Other LOD models: LOD_assume(), LOD_estimate_dPCR()