+.fn {dMod}

Direct sum of functions

Description

Used to add prediction function, parameter transformation functions or observation functions.

Usage

## S3 method for class 'fn'
x1 + x2

Arguments

x1

function of class obsfn, prdfn or parfn

x2

function of class obsfn, prdfn or parfn

Details

Each prediction function is associated to a number of conditions. Adding functions means merging or overwriting the set of conditions.

Value

Object of the same class as x1 and x2 which returns results for the union of conditions.

See Also

P, Y, Xs

Examples

# 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)