Create list for Kramer Chain Ladder parmaterization model g - Assumed loss emergence model, a function of the parameters a. Note g must be matrix-valued with size rows and size columns g itself Basic design is for g to be a function of a single parameter vector, however in the simulations it is necessary to work on a matrix of parameters, one row for each simulated parameter, so g_obj must be flexible enough to handle both. Here g_obj is nonlinear and based on the Kramer Chain Ladder parmaterization

Create list for Kramer Chain Ladder parmaterization model g - Assumed loss emergence model, a function of the parameters a. Note g must be matrix-valued with size rows and size columns g itself Basic design is for g to be a function of a single parameter vector, however in the simulations it is necessary to work on a matrix of parameters, one row for each simulated parameter, so g_obj must be flexible enough to handle both. Here g_obj is nonlinear and based on the Kramer Chain Ladder parmaterization

capecod(B0, paid_to_date, upper_triangle_mask)

Arguments

B0

development triangle
paid_to_date

numeric vector of length size. It is the lower diagnal of the development triangle in row order. It represents the amount paid to date.
upper_triangle_mask

is a mask matrix of allowable data, upper triangular assuming same development increments as exposure increments