| parameters | R Documentation |
The function either sets up a list of all parameters of a bamlss.frame, which
can be used for setting up models, or extracts the estimated parameters of a bamlss
object.
parameters(x, model = NULL, start = NULL,
fill = c(0, 1e-04), list = FALSE,
simple.list = FALSE, extract = FALSE,
...)
x |
A |
model |
The model name for which parameters should be initialized or extracted. |
start |
A named numeric vector which should be used when creating the parameter list.
See also function |
fill |
Numeric, when setting up a parameter list, the values the should be used for regression
coefficients (first element of |
list |
Should the function return a list of all parameters? |
simple.list |
Should the names of parameter vectors be dropped? |
extract |
Should parameters of a |
... |
Currently not used. |
Parameters for BAMLSS are used for optimizer functions in function bamlss.
The function is useful for initializing all parameters given a bamlss.frame
(which is done internally in function bamlss), but also for extracting all
estimated parameters of some optimizer.
The naming convention of the parameter list is used by a couple of functions in this package.
For each parameter of the modeled distribution, e.g., gaussian_bamlss has
parameters "mu" and "sigma", a list element is created. These elements the contain
the list of all model term parameters. Parametric model terms are indicated with "p" and
smooth model terms with "s". If the design matrix of a model term in the x list
of a bamlss.frame does not contain any columns names, then the parameters are named
with a leading "b", otherwise the column names of the design matrix are used. Smoothing
variances parameter vectors are named with a leading "tau2".
The naming convention is useful when setting up new model fitting engines for bamlss
and is used, e.g., by bfit and GMCMC, which are based on parameter
state list objects as provided by function bamlss.engine.setup.
A named list of all parameters of a bamlss.frame or bamlss
object.
bamlss.frame, bamlss, opt_bfit, sam_GMCMC,
get.par, set.par
## Create a "bamlss.frame"
set.seed(123)
d <- GAMart()
bf <- bamlss.frame(num ~ s(x1) + te(lon,lat), data = d)
## Create list of all parameters from "bamlss.frame".
p <- parameters(bf, list = TRUE)
str(p)
## Not run: ## Estimate model.
f <- list(num ~ s(x1) + te(lon,lat), sigma ~ s(x1))
b <- bamlss(f, data = d, sampler = FALSE)
## Extract estimated parameters.
parameters(b)
parameters(b, list = TRUE)
## End(Not run)
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