Question

HELP!!

In Matlab

The scenario is simple: A set of (x,y) data is available in the form of a simple text file – the first column represents x-values and the second column represents y-values. The task at hand is to provide the best model (or curve fit) to this set of data. Your application should provide the means to fit the following curve types to the data:

Linear (first order polynomial) of form (?? = ???? + ??) with non-zero ??-intercept

Linear (first order polynomial) of form (?? = ????) with zero ??-intercept

General polynomial of degree ??

Exponential

Power Law

Trigonometric

Logarithmic

Reciprocal

In addition, for each curve fit performed, your application should provide the Mean Square Error (MSE) between the raw data and the fitted curve. For both linear fits, your application should provide values of the coefficients of correlation R and of determination R2, as well.

Answer 1

SAVE THE FOLLOWING OCDE IN MATLABA ND GET THE RESULTS-

clc

clear

close all;

%% Linear Fit

x=1:10;

y1=x+randn(1,10);

scatter(x,y1,25,'g','*')

P=polyfit(x,y1,1);

yfit=P(1)*x+P(2);

hold on;

plot(x,yfit,'r-.');

12R0

%% Exponential

f = fit(x',y1','exp1');

figure

plot(f,x,y1)

12 10 นเ 11

%% Power fit

p=polyfit(log(x),log(y1),1);

a=p(1);

k=exp(p(2));

ezplot(@(x) k*x.^a,[x(1) x(end)])

%% Reciprocal Law

a1=lsqcurvefit(@(a1,x) a1(1)./x,1,x,y1);

figure

plot(x,y1,'o') %plot data

plot(x,a1./x) %fit

28