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 ...

This short course will provide an overview of non-parametric statistical techniques. The course will first describe what non-parametric statistics are, when they should be used, and their advantages ...

This article extends recent results [Scand. J. Statist. 28 (2001) 699] about exact non-parametric inferences based on order statistics with progressive type-II censoring. The extension lies in that ...

In general, there will be visible differences between a parametric and a nonparametric curve estimate. It is therefore quite natural to compare these in order to decide whether the parametric model ...

Nonparametric estimation and U-statistics have emerged as vital tools in modern statistical analysis, offering robust alternatives to traditional parametric methods. Nonparametric techniques bypass ...

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 ...

Please Note: Blog posts are not selected, edited or screened by Seeking Alpha editors. A lot of statistic analysis is based on parametric statistics. One of the most crucial assumptions is the bell ...

Parametric tests make assumptions that aspects of the data follow some sort of theoretical probability distribution. Non-parametric tests or distribution free methods do not, and are used when the ...