I have developed a predictive model in R which predicts a numerical value. To, check model accuracy, I have included root mean square error, root mean square error, bias and variance, calculated using functions inherited from the package "Metrics".
I am aware that low values of these statistics indicate a good model.
When its comes to comparing accuracy of two models, which statistic is to be considered for comparison? Is there any other test that should be performed to check accuracy?
I am new to predictive modelling, so I desire to know any other methods or tests to better indicate prediction accuracy and model comparison.