Fast-observation-error-function-continuous: Fast observation error function continuous Calculate the...

In adamkucharski/serosolver: Inference Framework for Serological Data

Fast observation error function continuous Calculate the probability of a set of observed antibody levels given a corresponding set of predicted antibody levels assuming continuous, bounded observations.

Description

Fast observation error function continuous Calculate the probability of a set of observed antibody levels given a corresponding set of predicted antibody levels assuming continuous, bounded observations.

Fast observation error function continuous with false positives Calculate the probability of a set of observed antibody levels given a corresponding set of predicted antibody levels assuming continuous, bounded observations. For true negatives (i.e., model predicts no infections), then the majority of the PDF is at min_measurement. There is a probability, fp_rate, of observing a value within the detectable range.

Usage

likelihood_func_fast_continuous(theta, obs, predicted_antibody_levels)

likelihood_func_fast_continuous_fp(theta, obs, predicted_antibody_levels)

Arguments

theta	NumericVector, a named parameter vector giving the normal distribution standard deviation and the max observable antibody level. Also a parameter fp_rate, giving the probability of a (uniformly distributed) false positive given true negative.
obs	NumericVector, the vector of observed log antibody levels
predicted_antibody_levels	NumericVector, the vector of predicted log antibody levels
a	vector of same length as the input data giving the probability of observing each observation given the predictions

Value

a likelihood for each observed antibody level

a likelihood for each observed antibody level

See Also

Other likelihood_functions: likelihood_func_fast()

Other likelihood_functions: likelihood_func_fast()

adamkucharski/serosolver documentation built on June 12, 2025, 9:08 a.m.