bamlss.engine.helpers | R Documentation |
These functions can be useful when setting up new model fitting engines that are based
on the setup function bamlss.engine.setup
. See the examples.
## Functions to extract parameter states.
get.par(x, what = NULL)
get.state(x, what = NULL)
set.par(x, replacement, what)
## Function for setting starting values.
set.starting.values(x, start)
x |
For function |
what |
The name of the parameter(s) that should be extracted or replaced. |
replacement |
The value(s) that should be used for replacement. |
start |
The named numeric vector of starting values. The name convention is based
on function |
bamlss.engine.setup
## Create a bamlss.frame.
d <- GAMart()
bf <- bamlss.frame(num ~ s(x1) + s(x2) + te(lon,lat), data = d, family = "gaussian")
names(bf$x$mu$smooth.construct)
## Use the setup function for
## adding state elements.
bf$x <- bamlss.engine.setup(bf$x, df = c("s(x1)" = 1, "s(x2)" = 3))
names(bf$x$mu$smooth.construct)
## Extract regression coefficients.
get.state(bf$x$mu$smooth.construct[["te(lon,lat)"]], "b")
## Extract smoothing variances.
get.state(bf$x$mu$smooth.construct[["te(lon,lat)"]], "tau2")
## More examples.
state <- bf$x$mu$smooth.construct[["te(lon,lat)"]]$state
get.par(state$parameters, "b")
get.par(state$parameters, "tau2")
state$parameters <- set.par(state$parameters, c(0.1, 0.5), "tau2")
get.par(state$parameters, "tau2")
## Setting starting values.
start <- c("mu.s.s(x1).b" = 1:9, "mu.s.s(x1).tau2" = 0.1)
bf$x <- set.starting.values(bf$x, start = start)
get.state(bf$x$mu$smooth.construct[["s(x1)"]], "b")
get.state(bf$x$mu$smooth.construct[["s(x1)"]], "tau2")
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