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Linear Regression gives NaN

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John Ziggs
John Ziggs 2021-5-20
评论： Star Strider 2021-5-20
Hi,
I am trying to do and plot a linear regression for the dataset attached. I tried following examples online, but I am getting NaN. This is my code and my data is attached.
clc
close all
clear all
%% Map
filename = 'TV_NYMA';
[num,string,vt] = xlsread(filename);
Year = num(:,1);
County = string(:,2);
VOC = num(:,3);
NOx = num(:,4);
CO = num(:,5);
PM25 = num(:,6);
Lat = num(:,7);
Lon = num(:,8);
%%
standard_NOx = normalize(NOx);
standard_VOC = normalize(VOC);
figure
scatter(standard_NOx,standard_VOC)
title('NOx vs VOC')
xlabel('NOx emissions standardized')
ylabel('VOC emissions standardized')
%%
X = [ones(length(standard_NOx),1) standard_NOx]
b = X\standard_VOC
regression_line = [ones(size(standard_NOx,1),1) standard_NOx]*b
I was wondering what am I doing wrong.
Thanks.
  2 个评论
dpb
dpb 2021-5-20
I didn't download the data, but why not
b=polyfit(standard_NOx,standard_VOC,1);
yhat=polyval(b,[min(standard_NOX) max(standard_NOX)]);
or, if have one of Statistics or Curve Fitting Toolboxes, there are other higher-level routines as well...
Just out of curiosity, did you look at what was returned for the coefficients matrix? Was it NaN there, already? IF so, there's probaby a NaN in the mix in the data somewhere.
John Ziggs
John Ziggs 2021-5-20
There indeed was an empty row in the dataset which caused the NaN. Thank you for your help! I appreciate it.

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采纳的回答

Star Strider
Star Strider 2021-5-20
Ran in:
There are 8 NaN values in those variables.
Eliminate them and it works —
T1 = readtable('https://www.mathworks.com/matlabcentral/answers/uploaded_files/625018/TV_NYMA.xlsx','VariableNamingRule','preserve')
T1 = 1803×8 table
Year County VOC Nox CO PM2.5 Lat Long ____ _________ _____ _____ ______ _____ ______ ______ 2010 {'BRONX'} 12.78 54.74 151.49 7.07 40.826 -73.92 2013 {'BRONX'} 0.33 7.03 5.01 0.44 40.826 -73.92 2013 {'BRONX'} 0.4 1.5 0.71 0.58 40.826 -73.92 2014 {'BRONX'} 0.33 10.94 5.37 0.45 40.826 -73.92 2015 {'BRONX'} 0.54 28.07 3.84 0.25 40.826 -73.92 2014 {'BRONX'} 0 0 0 0 40.826 -73.92 2014 {'BRONX'} 0.38 9.5 7.41 0.66 40.826 -73.92 2011 {'BRONX'} 0.11 7.88 1.97 0 40.826 -73.92 2013 {'BRONX'} 0.12 27.62 2.98 1.12 40.826 -73.92 2012 {'BRONX'} 6.4 67.55 40.88 1.68 40.826 -73.92 2014 {'BRONX'} 0.23 36.07 5.02 0.34 40.826 -73.92 2015 {'BRONX'} 0.35 8.47 6.16 0.52 40.826 -73.92 2016 {'BRONX'} 5.22 65.32 11.74 0 40.826 -73.92 2011 {'BRONX'} 0.42 1.65 0.69 0.9 40.826 -73.92 2013 {'BRONX'} 3.47 61.06 35.43 3.37 40.826 -73.92 2013 {'BRONX'} 0.43 5.71 4.38 0.39 40.826 -73.92
% Nox_Nan = nnz(isnan(T1.Nox))
% VOC_NaN = nnz(isnan(T1.VOC))
T1 = T1(~[isnan(T1.Nox) & isnan(T1.VOC)],:)
T1 = 1795×8 table
Year County VOC Nox CO PM2.5 Lat Long ____ _________ _____ _____ ______ _____ ______ ______ 2010 {'BRONX'} 12.78 54.74 151.49 7.07 40.826 -73.92 2013 {'BRONX'} 0.33 7.03 5.01 0.44 40.826 -73.92 2013 {'BRONX'} 0.4 1.5 0.71 0.58 40.826 -73.92 2014 {'BRONX'} 0.33 10.94 5.37 0.45 40.826 -73.92 2015 {'BRONX'} 0.54 28.07 3.84 0.25 40.826 -73.92 2014 {'BRONX'} 0 0 0 0 40.826 -73.92 2014 {'BRONX'} 0.38 9.5 7.41 0.66 40.826 -73.92 2011 {'BRONX'} 0.11 7.88 1.97 0 40.826 -73.92 2013 {'BRONX'} 0.12 27.62 2.98 1.12 40.826 -73.92 2012 {'BRONX'} 6.4 67.55 40.88 1.68 40.826 -73.92 2014 {'BRONX'} 0.23 36.07 5.02 0.34 40.826 -73.92 2015 {'BRONX'} 0.35 8.47 6.16 0.52 40.826 -73.92 2016 {'BRONX'} 5.22 65.32 11.74 0 40.826 -73.92 2011 {'BRONX'} 0.42 1.65 0.69 0.9 40.826 -73.92 2013 {'BRONX'} 3.47 61.06 35.43 3.37 40.826 -73.92 2013 {'BRONX'} 0.43 5.71 4.38 0.39 40.826 -73.92
standard_NOx = normalize(T1.Nox);
standard_VOC = normalize(T1.VOC);
X = [ones(length(standard_NOx),1) standard_NOx];
b = X\standard_VOC
b = 2×1
-0.0000 0.5010
regression_line = [ones(size(standard_NOx,1),1) standard_NOx]*b;
figure
plot(standard_NOx, standard_VOC, 'p')
hold on
plot(standard_NOx, regression_line, '-r')
hold off
grid
.
  2 个评论
John Ziggs
John Ziggs 2021-5-20
Thank you for your help! I should've realized the empty row in the data would cause the NaN. Thanks again!

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