MSfit | R Documentation |
MSfit
estimates a markov switching copula on a bivariate time series
of uniform marginal distributions.
MSfit(x, y, family = list(1, 1), initValues, tol = 1e-05)
x |
A numeric vector of uniform marginal values. |
y |
A numeric vector of uniform marginal values. |
family |
A list of integers specifying the family of the copula to use in each regime. |
initValues |
Sometimes optional numeric vector of starting values. See Details. |
tol |
A numeric value specifying the convergence tolerance of the model.
Specifically, the model reaches convergene if the difference in likelihood
from successive models falls below |
For initValues
, if the same copula family is used for each regime, no initial values
need to be supplied. If the user wants different copula families estimated
in different regimes, initValues need to be supplied. For a model with K
regimes, the order of the values should be provided as follows:
Copula parameters in the order they appear in family
K * (K - 1) transition variables: p_{1,1},...,p_{1,k-1},p_{2,1},...,p_{2,k-1},...,p_{k,k-1}
K - 1 initial state parameters: p_{0,1},...,p_{0,k-1}
MSfit
returns an S3 object of class
markovCopula
.
The summary, plot, coef, and logLik functions will, repectively, print a summarization of the output, a plot of dependence measures, extract model parameters, and extract the log-likelihood values.
An object of class markovCopula
has the following components:
log.likelihood | log-likelihood value for the regime |
pars | a vector of coefficients for the copula |
N | the length of the time-series |
solver | the final output from optim |
regime.inference | the model's condition density, conditional probability, conditional forecasts, and the smoothed probabilities |
copula | details of the estimated copulas in each regime |
transition | the transition matrix and initial regime vector |
nregimes | the number of regimes in the model |
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