Which of the following statements is not true? In kernel regression, a more flexible functional form (smaller bandwidth) leads to lower variance. Whereas, in series regression, a more flexible functional form (higher order polynomials) increases variance. Kernel and series regression models are both ways modeling nonlinear functional forms. In both the kernel and series regression framework, the optimal trade-off between bias and variance is found by minimizing the mean squared error, and/or other cross validation criterion. to balance the trade-off between bias and variance. Like in kernel regression models, series regression models have a trade-off between bias and variance