Usage
## Gradient boosting optimizer.
boost(x, y, family,
nu = 0.1, df = 4, maxit = 400, mstop = NULL,
verbose = TRUE, digits = 4, flush = TRUE,
eps = .Machine$double.eps^0.25, nback = NULL,
plot = TRUE, initialize = TRUE, ...)## Boosting summary extractor.
boost.summary(object, ...)
## Plot all boosting paths.
boost.plot(x, which = c("loglik", "loglik.contrib", "parameters"),
intercept = TRUE, spar = TRUE, mstop = NULL, name = NULL,
labels = NULL, color = NULL, ...)
## Boosting summary printing and plotting.
# S3 method for boost.summary
print(x, summary = TRUE, plot = TRUE,
which = c("loglik", "loglik.contrib"), intercept = TRUE,
spar = TRUE, ...)
# S3 method for boost.summary
plot(x, ...)
Arguments
x
For function boost()
the x
list, as returned from function
bamlss.frame
, holding all model matrices and other information that is used for
fitting the model. For the plotting function the corresponding bamlss
object
fitted with the boost()
optimizer. nu
Numeric, between [0, 1], controls the step size, i.e., the amount
that should be added to model term parameters.
df
Integer, defines the initial degrees of freedom that should be assigned
to each smooth model term. May also be a named vector, the names must match the model term
labels, e.g., as provided in summary.bamlss
. maxit
Integer, the maximum number of boosting iterations.
mstop
For convenience, overwrites maxit
.
name
Character, the name of the coefficient (group) that should be plotted. Note that
the string provided in name
will be removed from the labels on the 4th axis.
labels
A character string of labels that should be used on the 4 axis.
color
Colors or color function that creates colors for the (group) paths.
verbose
Print information during runtime of the algorithm.
digits
Set the digits for printing when verbose = TRUE
.
flush
use flush.console
for displaying the current output in the console. eps
The tolerance used as stopping mechanism, see argument nback
.
nback
Integer. If nback
is not NULL
, then the algorithm stops if the
the change in the log-likelihood of the last nback
iterations is smaller or
equal to eps
. If maxit = NULL
the maximum number of iterations is set to 10000.
plot
Should the boosting summary be printed and plotted?
initialize
Logical, should intercepts be initialized?
object
A bamlss
object that was fitted using boost()
. summary
Should the summary be printed?
which
Which of the three provided plots should be created?
intercept
Should the coefficient paths of intercepts be dropped in the plot?
spar
Should graphical parmeters be set with par
? …
For function boost()
, arguments passed to bamlss.engine.setup
.
for function boost.summary()
arguments passed to function print.boost.summary()
.