An autoregressive working dependence structure.
The dependence is defined in terms of the time component of the parent GEE class. Time represents a potentially multidimensional index from which distances between pairs of observations can be determined. The correlation between two observations in the same cluster is dep_params^distance, where dep_params is the autocorrelation parameter to be estimated, and distance is the distance between the two observations, calculated from their corresponding time values. time is stored as an n_obs x k matrix, where k represents the number of dimensions in the time index.
The autocorrelation parameter is estimated using weighted nonlinear least squares, regressing each value within a cluster on each preceeding value in the same cluster.
dist_func: function from R^k x R^k to R^+, optional :
B Rosner, A Munoz. Autoregressive modeling for the analysis of longitudinal data with unequally spaced examinations. Statistics in medicine. Vol 7, 59-71, 1988.
|covariance_matrix(endog_expval, index)||Returns the working covariance or correlation matrix for a given cluster of data.|
|covariance_matrix_solve(expval, index, ...)||Solves matrix equations of the form covmat * soln = rhs and returns the values of soln, where covmat is the covariance matrix represented by this class.|
|initialize(model)||Called by GEE, used by implementations that need additional setup prior to running fit.|
|update(params)||Updates the association parameter values based on the current regression coefficients.|