Description Usage Arguments Details Value References
View source: R/loglikelihood.R
mixing_weights_int
calculates the mixing weights of the specified GMAR, StMAR, or G-StMAR model
and returns them as a matrix.
1 2 3 4 5 6 7 8 9 10 11 12 |
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 |
parametrization |
is the model parametrized with the "intercepts" φ_{m,0} or "means" μ_{m} = φ_{m,0}/(1-∑φ_{i,m})? |
checks |
|
to_return |
should the returned object contain mixing weights for t=1,..,T ( |
The first p observations are taken to be the initial values.
to_return=="mw"
:a size ((n_obs-p)xM) matrix containing the mixing weights: for m:th component in m:th column.
to_return=="mw_tplus1"
:a size ((n_obs-p+1)xM) matrix containing the mixing weights: for m:th component in m:th column. The last row is for α_{m,T+1}
.
Galbraith, R., Galbraith, J. 1974. On the inverses of some patterned matrices arising in the theory of stationary time series. Journal of Applied Probability 11, 63-71.
Kalliovirta L. (2012) Misspecification tests based on quantile residuals. The Econometrics Journal, 15, 358-393.
Kalliovirta L., Meitz M. and Saikkonen P. 2015. Gaussian Mixture Autoregressive model for univariate time series. Journal of Time Series Analysis, 36, 247-266.
Meitz M., Preve D., Saikkonen P. 2021. A mixture autoregressive model based on Student's t-distribution. Communications in Statistics - Theory and Methods, doi: 10.1080/03610926.2021.1916531
Virolainen S. 2021. A mixture autoregressive model based on Gaussian and Student's t-distributions. Studies in Nonlinear Dynamics & Econometrics,doi: 10.1515/snde-2020-0060
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