dqstep: step size generator In Bhat: General likelihood exploration

Description

`dqstep` determines the smallest steps ds from s so that abs(f(s+ds)-f(s)) equals a pre-specified sensitivity

Usage

 `1` ```dqstep(x, f, sens) ```

Arguments

 `x` a list with components 'label' (of mode character), 'est' (the parameter vector with the initial guess), 'low' (vector with lower bounds), and 'upp' (vector with upper bounds) `f` the function that is to be minimized over the parameter vector defined by the list `x` `sens` target sensitivity (i.e. the value of f(s+ds)-f(s))

Details

uses simple quadratic interpolation

Value

returns a vector with the desired step sizes

Note

This function is part of the Bhat exploration tool

Author(s)

E. Georg Luebeck (FHCRC)

See Also

`dfp`, `newton`, `logit.hessian`

Examples

 ```1 2 3 4 5 6 7 8 9``` ``` ## Rosenbrock Banana function fr <- function(x) { x1 <- x[1] x2 <- x[2] 100 * (x2 - x1 * x1)^2 + (1 - x1)^2 } ## define x <- list(label=c("a","b"),est=c(1,1),low=c(0,0),upp=c(100,100)) dqstep(x,fr,sens=1) ```

Bhat documentation built on May 2, 2019, 6:41 a.m.