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Observe positive dPCR partition counts

Source: R/model_measurements.R
partitions_observe.Rd

This option fits the EpiSewer model to positive partition counts in digital PCR (dPCR), e.g. positive droplets in ddPCR, for the pathogen target of interest. This allows the use of a dPCR-specific likelihood using a Poisson distribution. For a more generic likelihood, see concentrations_observe().

Usage

partitions_observe(
  data,
  composite_window = 1,
  date_col = "date",
  positive_partitions_col = "positive_partitions",
  total_partitions_col = "total_partitions",
  replicate_col = NULL,
  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).

See also

Other observation types: concentrations_observe()