UtilIntrinsic2RSM: Convert from intrinsic to physical RSM parameters

In RJafroc: Artificial Intelligence Systems and Observer Performance

Convert from intrinsic to physical RSM parameters

Description

Convert intrinsic RSM parameters lambda_i and nu_i correspond to the physical RSM parameters lambda_i' and nu_i'. The physical parameters are more meaningful but they depend on mu. The intrinsic parameters are independent of mu. See book for details.

Usage

UtilIntrinsic2RSM(mu, lambda_i, nu_i)

Arguments

mu	The mean of the Gaussian distribution for the ratings of latent LLs, i.e. continuous ratings of lesions that were found by the search mechanism ~ N(μ,1). The corresponding distribution for the ratings of latent NLs is N(0,1).
lambda_i	The intrinsic Poisson lambda_i parameter.
nu_i	The intrinsic Binomial nu_i parameter.

Details

RSM is the Radiological Search Model described in the book. See also UtilRSM2Intrinsic.

Value

A list containing λ and ν

References

Chakraborty DP (2006) A search model and figure of merit for observer data acquired according to the free-response paradigm, Phys Med Biol 51, 3449–3462.

Chakraborty DP (2006) ROC Curves predicted by a model of visual search, Phys Med Biol 51, 3463–3482.

Chakraborty DP (2017) Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples, CRC Press, Boca Raton, FL. https://www.routledge.com/Observer-Performance-Methods-for-Diagnostic-Imaging-Foundations-Modeling/Chakraborty/p/book/9781482214840

Examples

mu <- 2;lambda_i <- 20;nu_i <- 1.1512925 
lambda <- UtilIntrinsic2RSM(mu, lambda_i, nu_i)$lambda 
nu <- UtilIntrinsic2RSM(mu, lambda_i, nu_i)$nu 
## note that the physical values are only constrained to be positive, but the physical variable nu
## must obey 0 <= nu <= 1

RJafroc documentation built on Nov. 10, 2022, 5:45 p.m.