Recent advances in nanotechnol. produced the 1st sensor transducers capable of resolving the adsorption and desorption of single mols. Examples include near IR fluorescent single-walled carbon nanotubes that report single-mol. binding via stochastic quenching. A central question for the theory of such sensors is how to analyze stochastic adsorption events and ext. the local concn. or flux of the analyte near the sensor. The authors compare algorithms of varying complexity for accomplishing this by 1st constructing a kinetic Monte Carlo model of mol. binding and unbinding to the sensor substrate and simulating the dynamics over wide ranges of forward and reverse rate consts. Methods involving single-site probability calcns., 1st and 2nd moment anal., and birth-and-death population modeling are compared for their accuracy in reconstructing model parameters in the presence and absence of noise over a large dynamic range. Overall, birth-and-death population modeling was the most robust in recovering the forward rate consts., with the 1st and 2nd order moment anal. very efficient when the forward rate is large (>10-3 s-1). The precision decreases with increasing noise, which the authors show masks the existence of underlying states. Precision is also diminished with very large forward rate consts., since the sensor surface quickly and persistently sats. (c) 2011 American Institute of Physics. [on SciFinder(R)]