prdfn: Prediction function
In dMod: Dynamic Modeling and Parameter Estimation in ODE Models

Description Usage Arguments Details Value Examples

A prediction function is a function x(..., fixed, deriv, conditions). Prediction functions are generated by Xs, Xf or Xd. For an example see the last one.

1	prdfn(P2X, parameters = NULL, condition = NULL)

`P2X`	transformation function as being produced by Xs.
`parameters`	character vector with parameter names
`condition`	character, the condition name

Prediction functions can be "added" by the "+" operator, see sumfn. Thereby, predictions for different conditions are merged or overwritten. Prediction functions can also be concatenated with other functions, e.g. observation functions (obsfn) or parameter transformation functions (parfn) by the "*" operator, see prodfn.

Object of class prdfn, i.e. a function x(..., fixed, deriv, conditions, env) which returns a prdlist. The arguments times and pars (parameter values) should be passed via the ... argument, in this order.

# Define a time grid on which to make a prediction by peace-wise linear function.
# Then define a (generic) prediction function based on thid grid.
times <- 0:5
grid <- data.frame(name = "A", time = times, row.names = paste0("p", times))
x <- Xd(grid)

# Define an observable and an observation function
observables <- eqnvec(Aobs = "s*A")
g <- Y(g = observables, f = NULL, states = "A", parameters = "s")

# Collect parameters and define an overarching parameter transformation
# for two "experimental condtions".
dynpars <- attr(x, "parameters")
obspars <- attr(g, "parameters")
innerpars <- c(dynpars, obspars)

trafo <- structure(innerpars, names = innerpars)
trafo_C1 <- replaceSymbols(innerpars, paste(innerpars, "C1", sep = "_"), trafo)
trafo_C2 <- replaceSymbols(innerpars, paste(innerpars, "C2", sep = "_"), trafo)

p <- NULL
p <- p + P(trafo = trafo_C1, condition = "C1")
p <- p + P(trafo = trafo_C2, condition = "C2")

# Collect outer (overarching) parameters and 
# initialize with random values
outerpars <- attr(p, "parameters")
pars <- structure(runif(length(outerpars), 0, 1), names = outerpars)

# Predict internal/unobserved states
out1 <- (x*p)(times, pars)
plot(out1)

# Predict observed states in addition to unobserved
out2 <- (g*x*p)(times, pars)
plot(out2)