scan_spline_dof {incidental} | R Documentation |
Scan spline degrees of freedom
Description
This function holds the regularization parameter value fixed and scans spline degrees of freedom.
Usage
scan_spline_dof(
reported,
delay_dist,
dof_grid,
method = "bic",
lam = 0,
regularization_order = 2,
reported_val = NULL,
end_pad_size = 0,
fisher_approx_cov = FALSE
)
Arguments
reported |
An integer vector of reported cases. |
delay_dist |
A positive vector that sums to one, which describes the delay distribution. |
dof_grid |
An integer vector of degrees of freedom for the spline basis. |
method |
Metric to choose "best" dof: 'aic', 'bic', 'val'. If method='val', reported_val must be non NULL and match reported size. |
lam |
A fixed value for the beta parameter regularization strength. |
regularization_order |
An integer (typically 0, 1, 2), indicating differencing order for L2 regularization of spline parameters. Default is 2 for second derivative penalty. |
reported_val |
Validation time series of equal size to reported vector for use with 'val' method. Default is NULL. |
end_pad_size |
And integer number of steps the spline is defined beyond the final observation. |
fisher_approx_cov |
A flag to use either the Fisher Information (TRUE) or the Hessian (FALSE) to approx posterior covariance over parameters. |
Value
A list of degree of freedom fit statistics:
best_dof = best degrees of freedom
dof_resdf = data frame of fit statistics (lambda, dof, aic, bic, val_lls, train_lls)