derivatives | R Documentation |
Derivatives of estimated smooths via finite differences
derivatives(object, ...) ## Default S3 method: derivatives(object, ...) ## S3 method for class 'gamm' derivatives(object, ...) ## S3 method for class 'gam' derivatives( object, term, data = newdata, order = 1L, type = c("forward", "backward", "central"), n = 200, eps = 1e-07, interval = c("confidence", "simultaneous"), n_sim = 10000, level = 0.95, unconditional = FALSE, frequentist = FALSE, offset = NULL, ncores = 1, partial_match = FALSE, ..., newdata = NULL )
object |
an R object to compute derivatives for. |
... |
arguments passed to other methods. |
term |
character; vector of one or more smooth terms for which
derivatives are required. If missing, derivatives for all smooth terms
will be returned. Can be a partial match to a smooth term; see argument
|
data |
a data frame containing the values of the model covariates at which to evaluate the first derivatives of the smooths. |
order |
numeric; the order of derivative. |
type |
character; the type of finite difference used. One of
|
n |
numeric; the number of points to evaluate the derivative at. |
eps |
numeric; the finite difference. |
interval |
character; the type of interval to compute. One of
|
n_sim |
integer; the number of simulations used in computing the simultaneous intervals. |
level |
numeric; |
unconditional |
logical; use smoothness selection-corrected Bayesian covariance matrix? |
frequentist |
logical; use the frequentist covariance matrix? |
offset |
numeric; a value to use for any offset term |
ncores |
number of cores for generating random variables from a
multivariate normal distribution. Passed to |
partial_match |
logical; should smooths be selected by partial matches
with |
newdata |
Deprecated: use |
A tibble, currently with the following variables:
smooth
: the smooth each row refers to,
var
: the name of the variable involved in the smooth,
data
: values of var
at which the derivative was evaluated,
derivative
: the estimated derivative,
se
: the standard error of the estimated derivative,
crit
: the critical value such that derivative
± (crit * se)
gives
the upper and lower bounds of the requested confidence or simultaneous
interval (given level
),
lower
: the lower bound of the confidence or simultaneous interval,
upper
: the upper bound of the confidence or simultaneous interval.
derivatives()
will ignore any random effect smooths it encounters in
object
.
Gavin L. Simpson
load_mgcv() dat <- data_sim("eg1", n = 400, dist = "normal", scale = 2, seed = 42) mod <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML") ## first derivatives of all smooths using central finite differences derivatives(mod, type = "central") ## derivatives for a selected smooth derivatives(mod, type = "central", term = "s(x1)") ## or via a partial match derivatives(mod, type = "central", term = "x1", partial_match = TRUE)
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