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 ...

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 ...

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 ...

Let τ be a prior distribution over the parameter space Θ for a given parametric model P θ, θ ∈ Θ. For the sample space X (over which P θ 's are probability measures) belonging to a general class of ...

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

Cardiometabolic diseases, such as heart attack, obesity, and diabetes, are responsible for nearly one-third of deaths ...

Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation The purpose of this paper is to compare in-sample and out-of-sample performances of three parametric and non-parametric ...

The landscape of the insurance industry is undergoing a transformative shift as climate change intensifies, bringing with it an increasing frequency and severity of natural disasters. Among the most ...