lnalik: Linear Noise Approximation log-likelihood.

In lnar: Inference for stochastic kinetic genetic networks.

Description

Estimates the log-likelihood of the LNA approximation.

Usage

lnalik(cout, nthetas, mydata, syssize = NA,
       relerr = 1e-09, abserr = 1e-09, method = 0, dfunction)

Arguments

cout	The parsed model.
nthetas	The vector of the parameters.
mydata	Either a matrix or a data frame of the data to be evaluated. The first column is assumed to correspond to the time of each observation.
syssize	Optional, a scalar indicating the system size.
relerr	Optional, a scalar indicating the relative error for the ODE solver.
abserr	Optional, a scalar indicating the absolute error for the ODE solver.
method	Optional, a scalar with possible options: 0: Restarting method using concentrations. The parameters are assumed to be scaled, i.e. thetas. 1: Restarting method using number of molecules. The parameters are assumed to be un-scaled, i.e. c. 3: Non-Restarting method using concentrations. The parameters are assumed to be scaled as well.
dfunction	The compiled model.

Details

See Giagos (2010) for a discussion on the Restarting and the Non Restarting method.

Value

Returns the estimated log-likelihood.

Author(s)

Vasileios Giagos

References

Giagos, V.: 2010, Inference for auto-regulatory genetic networks using diffusion process approximations, Thesis, Lancaster University, 2010.

Examples

## Not run: 
require(lnar)
tt <- matrix(c(1,-1,0,0,1,-1),nrow=2,ncol=3,byrow=TRUE)
rfun <- c("con1 * Prey","con2 * Prey * Predator","con3 * Predator")
thetas <- paste("con",1:3,sep="")
species <- c("Prey","Predator")
cout <- parsemod(tt,rfun,thetas,species)

mydata<-c(0.0, 5000.0, 3000, 1, 5989, 2992, 2, 7165, 3107, 3, 8534,
          3306,4, 10041, 3709, 5, 11624, 4265, 6, 13306, 5181, 7,
          14741, 6492,8, 15867, 8337, 9, 16025, 10981)

mydata2 <- matrix(mydata,10,3,byrow=TRUE)#Example dataset

compmod(cout,"derivs")

#Our initial values
nthetas<-c(.25,.20,0.125)

print(derivs(mydata[1],c(mydata[2],mydata[3],
                         c(0,0,0,0,0)),rep(0,7),nthetas))

(l1<-lnalik(cout,nthetas=nthetas, mydata=mydata2, method=1,
              relerr=1e-9, abserr=1e-9,
              dfunction=derivs) )
nthetas2<-c(.25,.20/8000,0.125)
(l2<-lnalik(cout,nthetas=nthetas2, mydata=mydata2, method=0,
              relerr=1e-9, abserr=1e-9,
              dfunction=derivs) )

## End(Not run)

lnar documentation built on May 2, 2019, 4:51 p.m.