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 is a preview. Log in through your library . Abstract In model selection literature, two classes of criteria perform well asymptotically in different situations: Bayesian information criterion ...

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 ...

An introduction to analysing quantitative data including topics such as, understanding the distribution of data variables, and parametric and non-parametric statistical tests. Data refers to numbers, ...

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 ...

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 ...

We provide novel, high-order accurate methods for non-parametric inference on quantile differences between two populations in both unconditional and conditional settings. These quantile differences ...