Altering design matrix for 'real' covariate
Posted: Fri Sep 24, 2021 1:04 pm
Hi all,
I'm attempting to add a linear constraint to my recovery probability estimates in a dead recovery (Brownie) model using MARK GUI. I have 17 sampling intervals, and want survival to be time-invariant, but recovery probabilities to be constrained by a 'real' covariate I've supplied.
I've reconstructed the design matrix, but do not think I have done it correctly. I've had trouble uploading a picture of my design matrix so I'll try and describe it:
The design matrix has three columns (S_intercept, f_intercept, f_cov) and of course the Parm. For my S_intercept column, I've placed 1's for the first 16 rows pertaining to my survival estimates, and zeros for the rest of the rows. My f_intercept column contains the opposite configuration (zeros for the first 16 rows, and 1s for the next 17 rows). The f_cov column contains zeros for the first 16 rows pertaining to the survival estimates, and the 'real' data for the next 17 rows pertaining to the recovery probabilities.
Does this sound even remotely correct? Any suggestions would be greatly appreciated!
I'm attempting to add a linear constraint to my recovery probability estimates in a dead recovery (Brownie) model using MARK GUI. I have 17 sampling intervals, and want survival to be time-invariant, but recovery probabilities to be constrained by a 'real' covariate I've supplied.
I've reconstructed the design matrix, but do not think I have done it correctly. I've had trouble uploading a picture of my design matrix so I'll try and describe it:
The design matrix has three columns (S_intercept, f_intercept, f_cov) and of course the Parm. For my S_intercept column, I've placed 1's for the first 16 rows pertaining to my survival estimates, and zeros for the rest of the rows. My f_intercept column contains the opposite configuration (zeros for the first 16 rows, and 1s for the next 17 rows). The f_cov column contains zeros for the first 16 rows pertaining to the survival estimates, and the 'real' data for the next 17 rows pertaining to the recovery probabilities.
Does this sound even remotely correct? Any suggestions would be greatly appreciated!