Why am I getting the same R-squared values?

Hello, I have a littel problem, when i use fitlm() i keep on getting the same same values for different models. I thought my original models were the wrong ones but I tried with known models as shown in the code attached. I keep on getting the same R-squared values for all the models of which am sure that should not be the case, is there a problem with my code? Please check and assist. Beacsue I suspect maybe there is something wrong with my code. I have attached a sample data below and also via google doc with link provided here https://docs.google.com/spreadsheets/d/10rK3bswrKyG_BiLRNHtIDBF6vEKo-zdzDTtdPu7KRd8/edit?usp=sharing

%Wind_data =25*rand(100000,1);
A=input('enter wind speed matrix\n')
 %second phase of filtration
nrows= numel(A);
ncols=1;
for i=1:nrows
    for j=1:ncols
        if A(i,j)<0
            A(i,j)=0.1;
        elseif A(i,j)>25
            A(i,j)=25;
        elseif A(i,j)==0
            A(i,j)=0.5;
        else
        end
    end 
end
Wind_data=A;
Param_rayl=raylfit(sort(Wind_data),0.05);
Ray_pdf = raylpdf(sort(Wind_data),Param_rayl);
Ray_cdf = raylcdf(sort(Wind_data),Param_rayl);
figure
%plot(sort(Wind_data),Ray_pdf)
%figure
%plot(sort(Wind_data),Ray_cdf)

%Inverse Weibull
[Params_weibull]=wblfit(Wind_data);
Weibull_inv=wblinv(sort(Wind_data),Params_weibull(1),Params_weibull(2));%cdf of inverse weibull
figure
%plot(sort(Wind_data),Weibull_inv);

%gamma probability density distribution
[Param_gamma]=gamfit(sort(Wind_data))%prarameters determination
Gamma_pdf=gampdf(sort(Wind_data),Param_gamma(1),Param_gamma(2));%gama pdf
Gamma_cdf=gamcdf(sort(Wind_data),Param_gamma(1),Param_gamma(2));%gamma cdf
%figure
%plot(sort(Wind_data),Gamma_pdf);
%figure
%plot(sort(Wind_data),Gamma_cdf);

%extreme value distribution
[Params_evpdf]=evfit(sort(Wind_data));
Gumbel_evpdf=evpdf(sort(Wind_data),Params_evpdf(1),Params_evpdf(2));
Gumbel_evcdf=evcdf(sort(Wind_data),Params_evpdf(1),Params_evpdf(2));
%figure
%plot(sort(Wind_data),Gumbel_evpdf);
%figure
%plot(sort(Wind_data),Gumbel_evcdf);

Combined_cdfs=[Ray_cdf Gamma_cdf Gumbel_evcdf];
Empc=ecdf(Wind_data);
%weibull cumulative

%group the Estc1
figure
Hs_ray=histogram(Ray_cdf,numel(Empc));
binEdges_ray = Hs_ray.BinEdges;
x1 = binEdges_ray(1:end-1) + Hs_ray.BinWidth/2;
R1=fitlm(Empc,x1')

%group the Estc_gamma
figure
Hs_gamma=histogram(Gamma_cdf,numel(Empc));
binEdges_gamma = Hs_gamma.BinEdges;
x2 = binEdges_gamma(1:end-1) + Hs_gamma.BinWidth/2;
R2=fitlm(Empc,x2')

%group the Estc_gamma
figure
Hs_gumbell=histogram(Gumbel_evcdf,numel(Empc));
binEdges_gumbell = Hs_gumbell.BinEdges;
x3 = binEdges_gumbell(1:end-1) + Hs_gumbell.BinWidth/2;
R3=fitlm(Empc,x3')
%trial-visualizaion
figure
cdfplot(Wind_data)
hold on
plot(sort(Wind_data),Ray_cdf)
plot(sort(Wind_data),Gamma_cdf)
plot(sort(Wind_data),Gumbel_evcdf);
hold off
legend('real','Ray','Gama','Gumbel')

[Torsten]

Please attach your wind speed data here using the paperclip button.

[okoth ochola]

Hello @Torsten, I have attached the data as above. Thank you for your assistance.

[Torsten]

What do the -9998 data in the second column for windspeed mean ?

And could you change your code such that the data are read into the matrix A ?

[okoth ochola]

-9998 is an entry treated as anomally, which has been taken care of by the loop in the code.

Pertaining to the second question; yes, it is possible if I used the xlsxread() function, but that would mean I give the path to the code based on where the data is stored in my computer. But I may not be aware where the data would be stored in another person's computer. At least that is the way am aware of, am yet to learn other ways too.

if there be another way, I really be eager to learn. Thank you

[Torsten]

You don't need to give the path on your computer - you only have to use the file name under which you saved the data here under MATLAB online ("sorted data for importig.csv") . And you have to remove the rows where -9998 appears - I guess you don't want to use this value as tremendous negative wind speed in the fitting process.

[dpb]

L=readlines('sorted data for importig.csv');
L(1:5)

ans = 5x1 string array
    "dateTimeUTC,windspeed (m/s)"
    "7/26/2017 22:00,0.61"
    "7/26/2017 23:00,0.46"
    "7/27/2017 0:00,0.48"
    "7/27/2017 1:00,0.81"

tW=readtable('sorted data for importig.csv','readvariablenames',1);

Warning: Column headers from the file were modified to make them valid MATLAB identifiers before creating variable names for the table. The original column headers are saved in the VariableDescriptions property.
Set 'VariableNamingRule' to 'preserve' to use the original column headers as table variable names.

head(tW)

      dateTimeUTC       windspeed_m_s_
    ________________    ______________

    07/26/2017 22:00         0.61     
    07/26/2017 23:00         0.46     
    07/27/2017 00:00         0.48     
    07/27/2017 01:00         0.81     
    07/27/2017 02:00         0.92     
    07/27/2017 03:00          0.6     
    07/27/2017 04:00         0.92     
    07/27/2017 05:00         1.07     

tW.Properties.VariableNames={'Date','WindSpeed'};
[height(tW) any(tW.WindSpeed==-9998) nnz(tW.WindSpeed==-9998) nnz(tW.WindSpeed>=0)]

ans = 1×4

34634 1 918 33716

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all(isfinite(tW.WindSpeed))

ans = logical
   1

tW=tW(tW.WindSpeed>=0,:);       % keep only valid data
WS=sort(tW.WindSpeed);
Param_rayl=raylfit(WS,0.05);
Ray_pdf = raylpdf(WS,Param_rayl);
Ray_cdf = raylcdf(WS,Param_rayl);
[Params_weibull]=wblfit(WS);

Rsq = 0.3437

Wei_pdf=wblpdf(WS,Params_weibull(1),Params_weibull(2));
histogram(WS,'Normalization','pdf');

Rsq = 0.3410

line(WS,Ray_pdf,'linestyle','-','color','r')
line(WS,Wei_pdf,'linestyle','-','color','b')
xlim([0 10])
legend('Rayleigh','Weibull')
xlabel('Windspeed'), ylabel('P(WS)')

As to the original Q?, R-sq is not an appropriate measure for distribution fitting testing; see <NIST> for a comparison of continuous distribution test statistics.