Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 20, No. 2 (Jun., 1992), pp. 171-185 (15 pages) A method for nonparametric estimation of density based on a randomly ...

Nonparametric methods form an important core of statistical techniques and are typically used when data do not meet parametric assumptions. Understanding the foundation of these methods, as well as ...

Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...

We introduce a non-parametric estimator of the diffusion coefficient of a diffusion process using a projection method on a wavelets orthonormal basis of L2( R). The sample path is observed at discrete ...