demo/exampleBDEN_GP.R

In Newmi1988/seeds: Estimate Hidden Inputs using the Dynamic Elastic Net

library(deSolve)

uvbParameter = c(  ks1=0.23,
                   ks2=4.0526,
                   kdr1=0.1,
                   kdr2=0.2118,
                   k1=0.0043,
                   k2=161.62,
                   ka1=0.0372,
                   ka2=0.0611,
                   ka3=4.7207,
                   kd1=94.3524,
                   kd2=50.6973,
                   kd3=0.5508,
                   ks3=0.4397,
                   kdr3=1.246,
                   uv=1,
                   ka4=10.1285,
                   kd4=1.1999,
                   n1=3,
                   n2=2,
                   n3=3.5,
                   kdr3a=0.9735,
                   kdr3b=0.406,
                   ksr=0.7537,
                   fhy3_s=5)

x0 = c(0.2,10,2,0,0,20,0,0,0,4.2,0.25,20,0)+0.00001

uvbModel <- function(t,x,parameters) {
  with (as.list(parameters),{
    
    dx1 = ((-2) * ((ka1 * (x[1]^2) * (x[4]^2)) - (kd1 * x[5])) + 
             (-2) * ((ka2 * (x[1]^2) * x[2]) - (kd2 * x[3])) + 
             ((ks1 *((1) + (uv * n3 * (x[11] + fhy3_s))))  - 
                (kdr1 * ((1) + (n1 * uv)) * x[1])))
    dx2 = ((-1) * ((ka2*(x[1]^2) * x[2]) - (kd2 * x[3])) +
             (-1) * ((ka4 * x[2] * x[12]) - (kd4 * x[13])))
    dx3 = (((ka2 * (x[1]^2) * x[2]) - (kd2*  x[3]))) 
    dx4 = ((-2) * (k1*(x[4]^2)) + (2) * (k2 * x[6]) + 
             (-2) * ((ka1 * (x[1]^2)* (x[4]^2)) - (kd1 * x[5])) +
             (-1)* (ka3 * x[4] *x[7]))
    dx5 =  (((ka1 * (x[1]^2) * (x[4]^2)) -(kd1 * x[5])))
    dx6 = ((-1) * (k2 * x[6]) +  (k1 * (x[4]^2)) +(kd3 * (x[8]^2)))
    dx7 = ((-1) * (ka3 * x[4] * x[7]) + ((ks2 * ((1) + (uv * x[5]))) - 
                                           (kdr2 * x[7])) + (2) * (kd3 * (x[8]^2)))
    dx8 = ((-2) * (kd3 * x[8]^2) + (ka3 * x[4] * x[7])) 
    dx9  = 0 
    dx10 = 0
    dx11 =  (((ks3 * ((1) + (n2 * uv))) -(kdr3 * (((x[3] / (kdr3a + x[3])) + 
                                                     (x[13] / (kdr3b + x[13]))) -(x[5] / (ksr + x[5]))) *  x[11])))
    dx12 = ((-1) * (ka4 * x[2] * x[12]) + (kd4 * x[13]))
    dx13 =((ka4 * x[2] * x[12]) - (kd4 * x[13]))
    
    list(c(dx1,dx2,dx3,dx4,dx5,dx6,dx7,dx8,dx9,dx10,dx11,dx12,dx13))
  })
}


uvbMeasure <-   function(y,parameter){
  
  y1 = 2*y[,5] + y[,4] + y[,8]
  y2 = 2*y[,5] + 2* y[,3] + y[,1]
  y3 = y[,6]
  y4 = y[,11]
  y5 = y[,4]
  
  return(cbind(y1,y2,y3,y4,y5))
}
  

y <- uvbData[,1:6]
t <- uvbData$t
sd <- uvbData[,7:11]


Model <- odeModel(func = uvbModel, parms = uvbParameter,times=c(0.025), 
                         measFunc = uvbMeasure, y = x0, meas = y, sd = sd,custom=TRUE)



A <- BDEN(odeModel          = Model,
          lambda            = .001,
          beta_init         = c(1,1,1,1,1),
          numbertrialsstep  = 15,
          numbertrialseps   = 2000,
          numbertrialinner  = 10)