The article explores new types of models for isotropic covariance functions, which are important in many practical applications. These new models are more flexible than traditional ones, allowing for both positive and negative covariance values in different parts of their domain. They can also exhibit different behaviors near the origin, such as parabolic or linear. The researchers have shown that these new models have a simple structure and can be easily applied to various real-world scenarios, making them valuable tools for practitioners.