LangmuirModel-class: S4 class of the SPR Langmuir model
In ffeng23/SPRATS: An R package to do Two state modelling of SPR data

Langmuir model object

check the manual for the detailed model specifications http://

kon: numeric association rate constant
koff: numeric dissociation rate constant
analyteConcentrations: numeric vector for different analyte concentrations.
s_d: numeric standard deviation of the Gaussian noise. by default s_d=0, which there is no noise.
Rmax: numeric the maximum RUs levels at the infinite high analyte concentration. It is also the maximum level of ligand immobilized on the chip surface
associationLength: numeric the time period to run the association
dissociationLength: numeric the time period to run the dissociation
R0: numeric vector the starting RUs for the dissocaiton phase. optional
offset: the level shifted at the begining of the dissociation phase optional
Rligand: the levels of ligand immobilized on the chip surface. optional
If this one is set, then it assumes a variable "Rmax" model. Where Rmax for different run is not fixed but rather different due to some factors such as regeration in (Sensiq) or stochasticity (in BioRad Proteon). In this model, the immoblized ligand is not fixed from run to run, but the effienciency or conversion constant is fixed.
This is a vector contains same number of element as the analyteConc.
efficiency: the conversion constant for a "variable" Rmax model optional
see above for explanation.