SSA.cat: Estimation of single catalytic constant using the stochastic...
In SIfEK: Statistical Inference for Enzyme Kinetics

Description Usage Arguments Details Value Examples

The function estimates single catalytic constant using single data set with an initial enzyme concentrations and substrate concentration. The stochastic simulation approximation method is utilized for the likelihood function.

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SSA.cat(method = T, time, species, enz, subs, MM, catal,
  nrepeat = 10000, jump = 1, burning = 0, catal_m = 1,
  catal_v = 1e+06)

`method`	method selection: T=TQ model, F=SQ model(default = T)
`time`	observed time interval
`species`	observed trajectory of product
`enz`	enzyme concentration
`subs`	substrate concentration
`MM`	true value of MM constant
`catal`	initial value of catalytic constant
`nrepeat`	total number of iteration (default=10000)
`jump`	length of distance (default =1)
`burning`	lenth of burning period (default =0)
`catal_m`	prior mean of gamma prior (default =1)
`catal_v`	prior variance of gamma prior (default =1e+6)

The function SSA.cat generates a set of Monte Carlo simulation samples from the conditional posterior distribution of catalytic constant of enzyme kinetics model. As the catalytic constant is only parameter to be estimated in the function the user should assign MM constant as well as initial enzyme concentration and substrate concentration. The prior information for the parameter can be given.

A vector of posterior samples of catalytic constant

data("Chymo_low")
time1=Chymo_low[,1]
species1=Chymo_low[,2]
Chymotrypsin.low<-SSA.cat(method=TRUE,time=time1,species=species1,enz=4.4e+7,subs=4.4e+7
                 ,MM=4.4e+8, catal=0.1,nrepeat = 10000)