Hello there,
I have a question regardind fitting model to data. I have 3 models, my problem is with time constant. Time constant parameters that are coming out of time vector, T, rather than parameter vector, P. This effectively gives them fixed values for time constants that are far too low. All of the models should fit the data fairly well. I ccould not figure it out and need help.
Main code is
close all; clear all;
% SET CALIBRATION CONSTANT
CF = 2.1931;
% LOAD DATA FILE
[fname,pname] = uigetfile('*.txt','LOAD DATA FILE');
DAT = dlmread([pname,'\',fname]);
% TIME IS COLUMN 1, DISPLACEMENT IS COLUMN 2
TIME = DAT(:,1);
DISP = CF*DAT(:,2); % APPLY CALIBRATION TO DISPLACEMENT
% CLIP AT 59.9s
IN = find(TIME >= 59.9);
TIME = TIME(IN);
DISP = DISP(IN);
% ZERO INITIAL AND FLIP DISPLACEMENT
TIME = TIME - TIME(1);
DISP = -DISP + DISP(1);
Y=DISP;
% DEFINE FUNCTION
[YM1] = MODEL_1(TIME,Y);
[YM2] = MODEL_2(TIME,Y);
[YM3] = MODEL_3(TIME,Y);
YM=[YM1 YM2 YM3];
My model function is
function [YM1] = MODEL_1(TIME,Y)
MODEL = @(P,T) P(1)+P(2).*(1-exp(-T./T(3)));
P0 = [0,1,1]; % INITIAL GUESS VALUES FOR PARAMETERS
PF = lsqcurvefit(MODEL,P0,TIME,Y);
YM1 = MODEL(PF,TIME);
% CALCULATE ADJUSTED R^2 HERE
Ybar = mean(Y); % AVERAGE OBSERVED
SStot = sum( (Y - Ybar).^2 ); % TOTAL SUM OF SQUARES
SSres = sum( (Y - YM1).^2 ); % RESIDUAL SUM OF SQUARES
R2 = 1 - SSres/SStot; % R SQUARED
n = length(Y); % NUMBER OF OBSERVATIONS
p = length (PF); % NUMBER OF PARAMETERS
Rbar2 = 1 - (1 - R2)*(n - 1)/(n - p - 1);
disp(['R^2 = ',num2str(R2),', ADJUSTED R^2 = ',num2str(Rbar2)])
end
and main code is
close all; clear all;
% SET CALIBRATION CONSTANT
CF = 2.1931;
% LOAD DATA FILE
[fname,pname] = uigetfile('*.txt','LOAD DATA FILE');
DAT = dlmread([pname,'\',fname]);
% TIME IS COLUMN 1, DISPLACEMENT IS COLUMN 2
TIME = DAT(:,1);
DISP = CF*DAT(:,2); % APPLY CALIBRATION TO DISPLACEMENT
% CLIP AT 59.9s
IN = find(TIME >= 59.9);
TIME = TIME(IN);
DISP = DISP(IN);
% ZERO INITIAL AND FLIP DISPLACEMENT
TIME = TIME - TIME(1);
DISP = -DISP + DISP(1);
Y=DISP;
% DEFINE FUNCTION
[YM1] = MODEL_1(TIME,Y);
[YM2] = MODEL_2(TIME,Y);
[YM3] = MODEL_3(TIME,Y);
YM=[YM1 YM2 YM3];
