predict_curve: Predict individual curves
In larslau/pavpop: Phase and amplitude varying population pattern models

This function predicts individual curves given the estimated parameters and predicted warps.

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predict_curve(t_p, t, y, basis_fct, c, warp_fct, w = NULL, amp_cov = NULL,
  amp_cov_par = NULL, amp_fct = NULL, warp_cov = NULL,
  warp_cov_par = NULL, deriv = FALSE, verbose_output = FALSE)

`t_p`	evaluation points for prediction.
`t`	observation points.
`y`	observation values.
`basis_fct`	basis function to describe the mean function.
`c`	weights for basis functions.
`warp_fct`	warping function.
`w`	warping parameters (optional). If parameters are not supplied, they are predicted from the parameter estimates in the model.
`amp_cov`	amplitude covariance matrix function.
`amp_cov_par`	amplitude covariance parameters.
`amp_fct`	functional basis that amplitude variation should be expressed in. If used, it is assumed that iid. Gaussian noise is present in the data.
`warp_cov`	warp covariance matrix function. If `w` is supplied, the argument is ignored.
`warp_cov_par`	warp covariance parameters. If `w` is supplied, the argument is ignored.
`deriv`	logical. Should the derivative of the curve be predicted?
`verbose_output`	logical. Should output also include predicted warps, residuals and the value of the posterior w \| y.