Returns a list with two elements; an array of AICc scores indexed by the number of parameters in the model considered and a matrix of parameters with three rows, one for each model.
A 'dark' object.
Is a matrix with seven columns and at least one row. The values of each element can be zero.
This is a brute-force method to make a first estimate of the optimal model parameters.
The matrix 'P' holds rows of possible parameter values. Each row is passed to the 3, 5, and 7 parameter models and the sum of residuals squared is calculated for the given times (obj$time) and thresholds (obj$thrs). So for each row in 'P' there is a score for each model. Then for each model the row which yields the lowest SSE is chosen as a starting point for optimisation. The optimised parameters are stored in 'param' and once the three parameter arrays have been found their AICc scores are found and returned as AIC.
Returns a list
An array of seven values with AIC scores at the index of model parameter count.
A three row by seven column matrix. Each row containing the optimised parameters for each model.
Jeremiah MF Kelly
Faculty of Life Sciences, The University of Manchester, M13 9PL, UK
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