Specifying a position of a Gaussian fit

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TTA
TTA 2022 年 12 月 21 日
コメント済み: Image Analyst 2022 年 12 月 23 日
Please how can I specify where my gaussian should be fitted on a data plot
Below is my matlab code and attahed are my sample plot with the data.
clear; clc;
thisfile = pwd + "\matlabdata.txt\";
Txtdata = load(thisfile);
x = Txtdata(:, 1);
y = Txtdata(:, 2);
inc=~isnan(y);
hgt = find(isnan(y));
gEqn = 'a*exp(-((x-b)/c)^2)+d';
startPoints = [5 0 10 2];
[fj,gof,output] = fit(x,y,gEqn,'Start', startPoints, 'Exclude', hgt);%,'Start', startPoints, 'Exclude', [1 10 25]
plot(fj,x,y)
The blue line is anexample of my desired Gaussian.
Its more of shifting a little bit the centre of the Gaussian side ways. I do not know if its possible
Thanks
  1 件のコメント
Mathieu NOE
Mathieu NOE 2022 年 12 月 22 日
Seems to me you want to "shape" your gaussian curve , not simply shift it
you have to first define which model would better fullfill your task

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Image Analyst
Image Analyst 2022 年 12 月 22 日
Seems like you blew past the posting guidelines. If you have any more questions, then attach 'matlabdata.txt' with the paperclip icon after you read this:
In the meantime see histfit
rng default; % For reproducibility
r = normrnd(10,1,1000,1);
pd = fitdist(r,'Normal')
pd =
NormalDistribution Normal distribution mu = 9.96737 [9.90538, 10.0294] sigma = 0.998965 [0.957021, 1.04478]
% Construct a histogram with a normal distribution fit.
plotParameters = histfit(r)
plotParameters =
2×1 graphics array: Bar Line
grid on
  5 件のコメント
TTA
TTA 2022 年 12 月 22 日
移動済み: Image Analyst 2022 年 12 月 23 日
Hi @Image Analyst, I have tried but still could not achieve what I want. I just wondering if its possible to achieve the black sketched line in the figure below. I also attached my code.
thanks
Image Analyst
Image Analyst 2022 年 12 月 23 日
What makes you think the black curve is better or more accurate than the red curve?
Maybe you should fit a different formula, like a Rayleigh or something. What is the theory behind this experiment? What formula does theory say your data should follow? In the middle range it just seems like total noise - a shotgun blast - like it follows no theoretical distribution whatsoever.

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