how to convert this code exposal to linear and how to find mape

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andrew moisidi 2021-5-29

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https://ww2.mathworks.cn/matlabcentral/answers/842960-how-to-convert-this-code-exposal-to-linear-and-how-to-find-mape

编辑： Walter Roberson 2025-3-11

function [a,g0] = getExpontialModel(f)
A = zeros(1,length(f)-1);
G_0 = zeros(1,length(f)-1);
for i=2:length(f)
    if f(i-1) ~= 0 
        A(i-1) = f(i)/f(i-1);
    else
        A(i-1) = 1;
    end
end
a = median(A); %more robust than mean function
for i=1:length(f)-1
    G_0(i) = f(i)/a^i;
end
g0 = median(G_0);%more robust than mean function

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Answer 1

Rahul 2025-3-11

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Hi @andrew moisidi,

In order to convert the exponential model to a linear model, consider using the logarithmic transformation. For this 'log' function can directly be used.

In order to fins the MAPE (Mean Absolute Percentage Error), a direct function is not availble in MATLAB in R2017b, however, it can be calculated using its formula. Here is an example:

g0 = median(G_0);
% Linearize the data
log_f = log(f);
    
% Calculate predicted values using the exponential model
predicted_f = g0 * a.^(0:length(f)-1);
% Calculate MAPE
mape = 100 * mean(abs((f - predicted_f) ./ f));