fnenvir {rmutil}R Documentation

Check covariates and parameters of a function

Description

fnenvir finds the covariates and parameters in a function and can modify it so that the covariates used in it are found in the data object specified by envir.

If the data object has class, repeated, times will use the response times as a covariate.

Usage

fnenvir(z, envir=sys.frame(sys.parent()), name=NULL, expand=TRUE)

Arguments

z A function.
envir The environment or data object of class, repeated, tccov, or tvcov, in which the function is to be interpreted.
name Character string giving the name of the data object specified by envir. Ignored unless the latter is such an object and only necessary when finterp is called within other functions.
expand If TRUE, expand functions with only time-constant covariates to return one value per observation instead of one value per individual. Ignored unless envir is an object of class, repeated.

Value

The (modified) function, of class formulafn, is returned with its attributes giving the (new) model function, the covariate names, and the parameter names.

Author(s)

J.K. Lindsey

See Also

finterp

Examples

fn <- function(p) a+b*x
fnenvir(fn)
fn <- function(p) a+p*x
fnenvir(fn)
x <- 1:4
fnenvir(fn)
fn <- function(p) p[1]+exp(p[2]*x)
fnenvir(fn)
#
y <- matrix(rnorm(20),ncol=5)
y[3,3] <- y[2,2] <- NA
resp <- restovec(y)
xx <- tcctomat(x)
z1 <- matrix(rnorm(20),ncol=5)
z2 <- matrix(rnorm(20),ncol=5)
z3 <- matrix(rnorm(20),ncol=5)
zz <- tvctomat(z1)
zz <- tvctomat(z2,old=zz)
reps <- rmna(resp, ccov=xx, tvcov=zz)
rm(y, x, z1, z2)
#
# repeated objects
func1 <- function(p) p[1]+p[2]*x+p[3]*z2
print(fn1 <- fnenvir(func1, envir=reps))
fn1(2:4)
#
# time-constant covariates
func2 <- function(p) p[1]+p[2]*x
print(fn2 <- fnenvir(func2, envir=reps))
fn2(2:3)
print(fn2a <- fnenvir(func2, envir=xx))
fn2a(2:3)
#
# time-varying covariates
func3 <- function(p) p[1]+p[2]*z1+p[3]*z2
print(fn3 <- fnenvir(func3, envir=reps))
fn3(2:4)
print(fn3a <- fnenvir(func3, envir=zz))
fn3a(2:4)
# including times
func3b <- function(p) p[1]+p[2]*z1+p[3]*z2+p[4]*times
print(fn3b <- fnenvir(func3b, envir=reps))
fn3b(2:5)
#
# with typing error and a variable not in the data object
func4 <- function(p) p[1]+p2[2]*z1+p[3]*z2+p[4]*z3
print(fn4 <- fnenvir(func4, envir=reps))
#
# first-order one-compartment model
# data objects for formulae
dose <- c(2,5)
dd <- tcctomat(dose)
times <- matrix(rep(1:20,2), nrow=2, byrow=T)
tt <- tvctomat(times)
# vector covariates for functions
dose <- c(rep(2,20),rep(5,20))
times <- rep(1:20,2)
# functions
mu <- function(p) {
        absorption <- exp(p[1])
        elimination <- exp(p[2])
        absorption*exp(-p[3])*dose/(absorption-elimination)*
                (exp(-elimination*times)-exp(-absorption*times))}
shape <- function(p) exp(p[1]-p[2])*times*dose*exp(-exp(p[1])*times)
# response
conc <- matrix(rgamma(40,shape(log(c(0.1,0.4))),mu(log(c(1,0.3,0.2)))),
        ncol=20,byrow=T)
conc[,2:20] <- conc[,2:20]+0.5*(conc[,1:19]-matrix(mu(log(c(1,0.3,0.2))),
        ncol=20,byrow=T)[,1:19])
conc <- restovec(ifelse(conc>0,conc,0.01))
reps <- rmna(conc, ccov=dd, tvcov=tt)
#
print(fn5 <- fnenvir(mu,envir=reps))
fn5(c(0,-1.2,-1.6))

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