model2.m

Incorporating Prior Knowledge in Cubic Spline Approximation - Application to the Identification of R

%Start
clear all
addpath '.\Libary'
load data_conc
load data_conc_big
cold = c;

M1 = [];
cycmax = 100;

%31, 0%
[P1,P2] = rawlsq(cold,t31,c31,0,0,[],1);
M1 = [M1, mean(P1)];

%31, 5%, yes
[P1,P2] = rawlsq(cold,t31,c31,0.05,0,[],cycmax);
M1 = [M1, mean(P1)];

%31, 5%, no
[P1,P2] = rawlsq(cold,t31,c31,0.05,1,[],cycmax);
M1 = [M1, mean(P1)];

%31, 10%, yes
[P1,P2] = rawlsq(cold,t31,c31,0.10,0,[],cycmax);
M1 = [M1, mean(P1)];

%31, 10%, no
[P1,P2] = rawlsq(cold,t31,c31,0.10,1,[],cycmax);
M1 = [M1, mean(P1)];

%12, 0%
[P1,P2] = rawlsq(cold,t12,c12,0,0,[],1);
M1 = [M1, mean(P1)];

%12, 5%, yes
[P1,P2] = rawlsq(cold,t12,c12,0.05,0,[],cycmax);
M1 = [M1, mean(P1)];

%12, 5%, no
[P1,P2] = rawlsq(cold,t12,c12,0.05,1,[],cycmax);
M1 = [M1, mean(P1)];

%12, 10%, yes
[P1,P2] = rawlsq(cold,t12,c12,0.10,0,[],cycmax);
M1 = [M1, mean(P1)];

%12, 10%, no
[P1,P2] = rawlsq(cold,t12,c12,0.10,1,[],cycmax);
M1 = [M1, mean(P1)];

%End
M1
save model2 M1 M2
rmpath '.\Libary'