Why am I getting the same R-squared values?

Question

okoth ochola 2024-10-6

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2157690-why-am-i-getting-the-same-r-squared-values

评论： dpb 2024-10-6

sorted data for importig.csv

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')

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Torsten 2024-10-6

编辑：Torsten 2024-10-6

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 2024-10-6

在 MATLAB Online 中打开

sorted data for importig.csv

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

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.

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Why am I getting the same R-squared values?

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Why am I getting the same R-squared values?

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