Solving hotelling function code

Hello

I am trying to use the following code to implement the function T2Hot2ihe

[filename, pathname] = uigetfile('*.csv');

ogi = readtable(filename);

Bix = table2array(ogi);

[e] = T2Hot2ihe(Bix, 0.05);

The data in excel is

x y z

0.1 0.3 0.4

0.2 0.3 0.3

0.2 0.3 0.5

0.2 0.3 0.5

0.2 0.3 0.5

0.2 0.3 0.5

0.2 0.3 0.5

0.2 0.3 0.5

0.2 0.6 0.6

0.4 0.7 0.9

I am getting the error

Index exceeds the number of array elements (0).

Error in T2Hot2ihe (line 116)

r1=n(1);

Error in happier (line 6)

[e] = T2Hot2ihe(Bix, 0.05);

I will be grateful if anyone help me to overcome this error so that I can run the code.

Thanks in advance

The function is shown below:

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function [T2Hot2ihe] = T2Hot2ihe(X,alpha)

%Hotelling's T-Squared test for two multivariate independent samples

%with unequal covariance matrices.

%

% Syntax: function [T2Hot2ihe] = T2Hot2ihe(X,alpha)

%

% Inputs:

% X - multivariate data matrix.

% alpha - significance level (default = 0.05).

%

% Output:

% n1 - sample-size one.

% n2 - sample-size two.

% p - variables.

% T2 - Hotelling's T-Squared statistic.

% Chi-sqr. or F - the approximation statistic test.

% df's - degrees' of freedom of the approximation statistic test.

% P - Probability that null Ho: is true.

%

% For this test it is highly recommended both sample-sizes must be greater than 50.

% The Hotelling's T-Squared takes a Chi-square approximation.

%

% Example: For a two groups (g = 2) with three independent variables (p = 3) and

% considering unequal covariance matrices (tested by the MBoxtest function),

% we are interested to test any difference between its mean vectors with

% a significance level = 0.05.

% The two groups have the same sample-size, n1 = n2 = 5.

% Group

% ---------------------------------------

% 1 2

% ---------------------------------------

% x1 x2 x3 x1 x2 x3

% ---------------------------------------

% 23 45 15 277 230 63

% 40 85 18 153 80 29

% 215 307 60 306 440 105

% 110 110 50 252 350 175

% 65 105 24 143 205 42

% ---------------------------------------

%

% Total data matrix must be:

% X=[1 23 45 15;1 40 85 18;1 215 307 60;1 110 110 50;1 65 105 24;

% 2 277 230 63;2 153 80 29;2 306 440 105;2 252 350 175;2 143 205 42];

%

% Calling on Matlab the function:

% T2Hot2ihe(X)

% Immediately it ask:

% -Do you have an expected mean vector? (y/n):

% That for this example we must to put:

% n (meaning 'no')

% Otherwise (y; meaning 'yes') you must to give the expected mean vector.

% If both sample-sizes are less or equal to 50, the program gives the next:

% WARNING: For this test it is highly recommended both sample-sizes

% must be greater than 50.

%

% Answer is:

% WARNING: For this test it is highly recommended both sample-sizes must be greater than 50.

%

% -----------------------------------------------------------------------------

% n1 n2 Variables T2 Chi-sqr. df P

% -----------------------------------------------------------------------------

% 5 5 3 11.1037 11.1037 3 0.0112

% -----------------------------------------------------------------------------

% Mean vectors result significant.

%

%

% Created by A. Trujillo-Ortiz and R. Hernandez-Walls

% Facultad de Ciencias Marinas

% Universidad Autonoma de Baja California

% Apdo. Postal 453

% Ensenada, Baja California

% Mexico.

% [e-mail]

% And the special collaboration of the post-graduate students of the 2002:2

% Multivariate Statistics Course: Karel Castro-Morales, Alejandro Espinoza-Tenorio,

% Andrea Guia-Ramirez.

%

% Copyright (C) November 2002

%

% References:

%

% Johnson, R. A. and Wichern, D. W. (1992), Applied Multivariate Statistical Analysis.

% 3rd. ed. New-Jersey:Prentice Hall. pp. 238-241.

%

if nargin < 1,

error('Requires at least one input arguments.');

end;

if nargin < 2,

alpha = 0.05; %(default)

end;

if (alpha <= 0 | alpha >= 1)

fprintf('Warning: significance level must be between 0 and 1\n');

return;

end;

g = max(X(:,1)); %Number of groups.

n = []; %Vector of groups-size.

indice = X(:,1);

for i = 1:g

Xe = find(indice==i);

eval(['X' num2str(i) '= X(Xe,2:end);']);

eval(['n' num2str(i) '= length(X' num2str(i) ') ;'])

eval(['xn= n' num2str(i) ';'])

n = [n,xn];

end;

[f,c] = size(X);

X = X(:,2:c);

[N,p]=size(X);

r=1;

r1=n(1);

bandera=2;

for k=1:g

if n(k)>=20;

bandera=1;

end;

end;

if (n(1) <= p)|(n(2) <= p),

error('Requires that one of the sample-sizes must be greater than the number of variables (p).');

end;

ask=input('Do you have an expected means vector? (y/n): ','s');

if ask=='y'

mu=input('Give me the expected means vector: ');

else

mu=zeros([1,p]);

end;

r=1;

r1=n(1);

for k=1:g

eval(['S' num2str(k) '=cov(X(r:r1,:));';]); %Partition of the sample covariance matrices.

eval(['M' num2str(k) '= mean(X(r:r1,:));']); %Partition of the sample mean vectors.

if k < g

r=r+n(k);

r1=r1+n(k+1);

end;

end;

dM=(M1-M2)-mu;

T2=dM*inv((S1/n(1))+(S2/n(2)))*dM'; %Hotelling's T-Squared statistic.

if (n(1) < 50) | (n(2) < 50);

disp(' ')

disp('WARNING: For this test it is highly recommended both sample-sizes must be greater than 50.');

end

X2=T2;

v=p;

P=1-chi2cdf(X2,v); %probability that null Ho: is true.

disp(' ')

fprintf('--------------------------------------------------------------------------------\n');

disp(' n1 n2 Variables T2 Chi-sqr. df P')

fprintf('--------------------------------------------------------------------------------\n');

fprintf('%5.i%8.i%12.i%14.4f%15.4f%12.i%13.4f\n',n(1),n(2),p,T2,X2,v,P);

fprintf('--------------------------------------------------------------------------------\n');

if P >= alpha

disp('Mean vectors result not significant.');

else

disp('Mean vectors result significant.');

end

return;

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