Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...

Density estimation is a fundamental component in statistical analysis, aiming to infer the probability distribution of a random variable from a finite sample without imposing restrictive parametric ...

Several studies have predicted that not all geomagnetic reversals have been discovered, but it was unknown in which periods they might be hidden. Researchers led by the National Institute of Polar ...

We propose a method for reconstructing a probability density function (pdf) from a sample of an n-dimensional probability distribution. The method works by iteratively applying some simple ...

A dual-model battery health assessment framework analyzes real-world voltage data from retired EV batteries in grid storage. Using incremental capacity and probability density methods, it improves ...

A brief description of the methods used by the SYSLIN procedure follows. For more information on these methods, see the references at the end of this chapter. There are two fundamental methods of ...

Gas density is frequently estimated indirectly by gas pressure sensors. Because the pressure in a tightly sealed compartment fluctuates greatly with temperature, such systems require temperature ...

All methods for estimating the risk-neutral density from the volatility smile boil down to the completion of the implied volatility function by interpolating between available strike prices and ...