In particular, the finite Lie algebras give models with fractional filling fractions, while the indefinite ones classify models with negative filling fractions which can be associated with the physics of holes in the graphene.
Thus, by applying these two permittivity models with corresponding fractions for each medium to our problem (assuming that the known chemical substances are presented but with unknown ratios), the parameters are reduced to four unknowns.
We simulated constant rate birth-death models with extinction fractions ranging from low to very high (0.1, 0.5, and 0.9), and different taxon sampling proportions (25%, 50 %, 75, and 100%).
Results from forward fitting a regression model with genomic fractions of RR stretches from 546 chromosomes as response.
Results from forward fitting a regression model with genomic fractions of YR stretches from 546 chromosomes as response.
So numerical models with different volume fractions can be obtained easily.
Reflection models with a reflection fraction of ⩾15, and Comptonisation models with two components of different temperatures and optical depths (kT1 = 83 keV, T1 = 30 eV, τ1 = 0.8; KT2 = 3.5 keV, T2 = 60 eV, τ2 = 2.8) can be fit to the spectrum, but cannot be constrained.
The programs used to estimate the model parameters were the SAS macro for survival models with a cured fraction (Mixture Cure Models).
Models with a nonsusceptible fraction, estimated using the Weibull tail completion method (Table 6), gave very different estimates for the hazard ratio and the odds ratio, as compared with those based on the zero-tail completion method.
Thus, the models with a nonsusceptible fraction based on the zero-tail completion method, which assumes 0 hazard after the observed largest uncensored time to first event time, are not robust in this situation.
