This functions is a constructor for the cor_arma class, representing
an autoregression-moving average correlation structure of order (p, q).
cor_arma(formula = ~1, p = 0, q = 0, r = 0, cov = FALSE)A one sided formula of the form ~ t, or ~ t | g,
specifying a time covariate t and, optionally, a grouping factor g.
A covariate for this correlation structure must be integer valued.
When a grouping factor is present in formula, the correlation structure
is assumed to apply only to observations within the same grouping level;
observations with different grouping levels are assumed to be uncorrelated.
Defaults to ~ 1, which corresponds to using the order of the observations
in the data as a covariate, and no groups.
A non-negative integer specifying the autoregressive (AR) order of the ARMA structure. Default is 0.
A non-negative integer specifying the moving average (MA) order of the ARMA structure. Default is 0.
A non-negative integer specifying the autoregressive response (ARR) order. See 'Details' for differences of AR and ARR effects. Default is 0.
A flag indicating whether ARMA effects should be estimated
by means of residual covariance matrices
(currently only possible for stationary ARMA effects of order 1).
If FALSE (the default) a regression formulation
is used that is considerably faster and allows for ARMA effects
of order higher than 1 but cannot handle user defined standard errors.
An object of class cor_arma, representing an
autoregression-moving-average correlation structure.
AR refers to autoregressive effects of residuals, which is what is typcially understood as autoregressive effects. However, one may also model autoregressive effects of the response variable, which is called ARR in brms.
# NOT RUN {
cor_arma(~visit|patient, p = 2, q = 2)
# }
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