Description Usage Arguments Value
View source: R/standardErrors.R
standard_errors
numerically approximates standard errors for the given estimates of GMAR, StMAR, or GStMAR model.
1 2 3 4 5 6 7 8 9 10 11 12 13 |
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 φ denotes an AR coefficient, σ^2 a variance, α a mixing weight, and ν a degrees of
freedom parameter. If |
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 φ_{m,1},...,φ_{m,p} are restricted to be the same for all regimes. |
constraints |
specifies linear constraints imposed to each regime's autoregressive parameters separately.
The symbol φ denotes an AR coefficient. Note that regardless of any constraints, the autoregressive order
is always |
conditional |
a logical argument specifying whether the conditional or exact log-likelihood function should be used. |
parametrization |
is the model parametrized with the "intercepts" φ_{m,0} or "means" μ_{m} = φ_{m,0}/(1-∑φ_{i,m})? |
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 |
Returns approximate standard errors of the parameter values in a numeric vector.
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