To begin selecting models for time series data, conduct hypothesis tests for stationarity, autocorrelation, and heteroscedasticity. After estimating the models, compare the fits using, for example, information criteria or a likelihood ratio test. You can also assess whether the models violate any assumptions by analyzing the residuals. For a multiple linear regression model, you can assess whether there is a structural change in the model, or address heteroscedasticity when estimating the regression coefficients.