standard_errors {uGMAR} | R Documentation |
Calculate standard errors for estimates of a GMAR, StMAR, or G-StMAR model
Description
standard_errors
numerically approximates standard errors for the given estimates of GMAR, StMAR, or GStMAR model.
Usage
standard_errors(
data,
p,
M,
params,
model = c("GMAR", "StMAR", "G-StMAR"),
restricted = FALSE,
constraints = NULL,
conditional = TRUE,
parametrization = c("intercept", "mean"),
custom_h = NULL,
minval
)
Arguments
data |
a numeric vector or class |
p |
a positive integer specifying the autoregressive order of the model. |
M |
|
params |
a real valued parameter vector specifying the model.
Symbol |
model |
is "GMAR", "StMAR", or "G-StMAR" model considered? In the G-StMAR model, the first |
restricted |
a logical argument stating whether the AR coefficients |
constraints |
specifies linear constraints imposed to each regime's autoregressive parameters separately.
The symbol |
conditional |
a logical argument specifying whether the conditional or exact log-likelihood function should be used. |
parametrization |
is the model parametrized with the "intercepts" |
custom_h |
a numeric vector with the same length as |
minval |
this will be returned when the parameter vector is outside the parameter space and |
Value
Returns approximate standard errors of the parameter values in a numeric vector.