sphering transformation of adjusted r squared , sum of squared error and f statistic in matlab

To perform the sphering transformation on adjusted R-squared, sum of squared error, and F-statistic in MATLAB, you can use the following steps:

1. Calculate the value of adjusted R-squared, sum of squared error, and F-statistic.
2. Apply the sphering transformation to these values.

Here's an example MATLAB code that demonstrates these steps:

main.m
% Calculate adjusted R-squared, sum of squared error, and F-statistic
adj_r_squared = 0.8;
sse = 100;
f_statistic = 10;

% Apply sphering transformation
sphered_adj_r_squared = sqrt(adj_r_squared);
sphered_sse = sqrt(sse);
sphered_f_statistic = sqrt(f_statistic);

% Display the sphered values
disp('Sphered Adjusted R-squared: ' + string(sphered_adj_r_squared));
disp('Sphered Sum of Squared Error: ' + string(sphered_sse));
disp('Sphered F-statistic: ' + string(sphered_f_statistic));
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In this example, I assume that you have already calculated the values of adjusted R-squared, sum of squared error, and F-statistic. You can replace the placeholder values with your own calculations.

Note that the sphering transformation in this example is simply taking the square root of each of the original values. You can modify the code to apply a different transformation method if needed.

Please let me know if you have any further questions!