Linear regression on a semi-log scale

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Hi,
I'm trying to plot a linear regression line on a semi-log scale.
Y-axis Linear Received power in dB
X-axis Log distance in m
The program and data I'm using as as follows:
Inc=1;
D=10; %Max meaurement distance
d1=(1:Inc:D); %1m to max measurment distance (D) in Increments (Inc)
RXPdata1=[-45.0983; -53.3746; -54.4132; -56.8286; -59.2905; -60.2743; -60.6919; -59.4938; -64.0525; -62.6163]; %Measured data in dB
semilogx(d1,(RXPdata1(:,1)),'-or') %Plot measured data
hold on
%Graph Set up
title ('Plot showing measured data')
xlabel('Distance (m) [Log scale]')
ylabel('Recieved Power (dB)')
legend ('Measured Data','Location','EastOutside')
axis([0 10 -70 -35]);
hold on
grid on
Can anyone help?
James

采纳的回答

Miroslav Balda
Miroslav Balda 2013-6-11
The following code solves your problem:
% James.m
% JAMES Linear regression on a semilog scale
%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 2013-06-11
%
% Miroslav Balda
% miroslav AT balda DOT cz
%
Inc=1;
D=10; % Max meaurement distance
%
d1=(1:Inc:D); % 1m to max measurment distance (D) in Increments (Inc)
RXPdata1=[-45.0983; -53.3746; -54.4132; -56.8286; -59.2905; -60.2743;...
-60.6919; -59.4938; -64.0525; -62.6163]; % Measured data in dB
%
semilogx(d1,(RXPdata1(:,1)),'-or') % Plot measured data
hold on
%
% % Graph Set up
%
title ('Plot showing measured data','FontSize',14, 'FontWeight','bold')
xlabel('Distance (m) [Log scale]','FontSize',10, 'FontWeight','bold')
ylabel('Recieved Power (dB)','FontSize',10, 'FontWeight','bold')
%
axis([0 10 -70 -35]);
hold on
grid on
%
% Regression
%
logd1 = log10(d1');
A = [ones(size(RXPdata1)),logd1];
c = A\RXPdata1
y = A*c;
plot(d1,y,'o-', d1,y,'*-')
%
legend ('Measured Data','Lin. Regression','Location','EastOutside')
It is all. Good luck!
Mira
  2 个评论
James Mathew
James Mathew 2013-6-11
Mira,
Many many thanks, this has saved me hours of work!!!
James
James Mathew
James Mathew 2013-6-18
Mira,
Me again, any chance you could help me out again. If trying to find the following variables for the line:
- where the line intersects 0 (or it is 1?) - the gradient - the regression coefficient
Thanks in advance.
James

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