How to get RMSE, R-squared, and p-values from fitrgp?

I have trained a model on a table including dependent variable 'Arm' and 6 independent variables 'duration' + 'heading' + 'speed' + 'cur_speed' + 'tidalrange' + 'Hs', using the code below.

How to get the RMSE, R-squared value, and p-values from the model?

I have tried using 'gprMdl.Rsquared.Ordinary' and 'gprMdl.Rsquared.Adjusted' but it doesn't seem to work

gprMdl = fitrgp(tableTest,'Arms~duration+heading+speed+cur_speed+tidalrange+Hs',...
    'KernelFunction','squaredexponential','FitMethod','exact','PredictMethod',...
    'exact','Standardize',1)

yPredict = predict(gprMdl,tableTest) % Create model predictions

yActual = tableTest.Arms % Observed data 

residuals = yActual - yPredict % Calculate residuals

Answer 1

[Anurag]

Hi Tobenna,

I understand that being unable to use the inbuilt metrics you want to find a way to calculate RMSE, R-squared and p-values from your code. Refer to the following code for doing the same:

% Calculate RMSE (Root Mean Square Error)
RMSE = sqrt(mean(residuals.^2));

% Calculate R-squared
SSR = sum((yPredict - mean(yActual)).^2);  % Regression sum of squares
SST = sum((yActual - mean(yActual)).^2);   % Total sum of squares
R2 = SSR / SST;

Lastly, for p-values, you would typically need to use linear regression models or other models that provide statistical tests for variable significance. GPR doesn't inherently provide p-values because it's not a linear regression model.

Hope this helped,

Regards,

Anurag