eiparametrisistä
Eiparametrisistä refers to a specific type of statistical modeling that does not assume a particular functional form for the relationship between variables. In contrast to parametric models, which specify a fixed set of parameters to describe these relationships (e.g., a linear regression assuming a straight line), non-parametric methods allow the data itself to determine the shape of the model. This flexibility makes them particularly useful when the underlying data generating process is unknown or complex.
The core idea behind non-parametric statistics is to estimate functions or distributions without imposing strong assumptions
Non-parametric approaches are advantageous when dealing with noisy data or when exploring patterns that might be