Journal of Undergraduate Research
Parameter Estimation Using a Continuous, Differentiable and Asymmetric Penalized Likelihood Function
Keywords
parameter estimation, asymmetric penalized likelihood function, CPMS
College
Physical and Mathematical Sciences
Department
Statistics
Abstract
Per the original ORCA proposal, work has been done to estimate relative amounts of compounds from GC-MS (gas chromatography-mass spectrometry) data using an asymmetric penalized likelihood function. The initial results of this project were presented at the CPMS Student Research Conference in March of this year1. The results consist of a simulation study where we simulate the problem of co-eluting, or overlapping, compounds and attempt to apply basic regression techniques as well as the asymmetric penalty function to see how they compare. Under certain conditions the new penalty function has less bias, but overall the function is unstable. There are many parameters involved that must be optimized which leads to large variation in estimates. Further work might involve optimizing these parameters based on some selection criteria.
Recommended Citation
Holt, Brian and Tolley, Dr. Dennis
(2013)
"Parameter Estimation Using a Continuous, Differentiable and Asymmetric Penalized Likelihood Function,"
Journal of Undergraduate Research: Vol. 2013:
Iss.
1, Article 2818.
Available at:
https://scholarsarchive.byu.edu/jur/vol2013/iss1/2818