Spatiotemporal modeling of irregularly spaced aerosol optical depth data

Econometric Modeling of Multivariate Irregularly-Spaced High-Frequency Data

The recent advent of high frequency data provides researchers with transaction by transaction level data. Examples include scanner data from grocery stores or financial transactions data. These new data sets allow researchers to take an unprecedented look at the underlying economic structure of the markets. Often the hypothesis of interest is in the context of multivariate time series data. Ana...

Multiresolution Analysis Adapted to Irregularly Spaced Data

This paper investigates the mathematical background of multiresolution analysis in the specific context where the signal is represented by irregularly sampled data at known locations. The study is related to the construction of nested piecewise polynomial multiresolution spaces represented by their corresponding orthonormal bases. Using simple spline basis orthonormalization procedures involves...

Aerosol Optical Depth Spatial and Temporal Variability Using Satellite Data Over Indian Major Cities

Introduction: The study’s main aim is to investigate the long-term variation of Aerosol Optical Depth (AOD). It also aims to show the relationship between meteorological parameters. This study evaluates long-term (2010 to 2021) special and temporal changes over major Indian regions using satellite-based data from NASA’s Terra Satellite. Materials and Methods: This study was carried out during ...

Bayesian smoothing of irregularly-spaced data using Fourier basis functions

The spectral representation of Gaussian processes via the Fourier basis provides a computationally efficient specification of spatial surfaces and nonparametric regression functions in various statistical models. I describe the representation in detail and introduce the spectralGP R library for computations. Because of the large number of basis coefficients, some form of shrinkage is necessary;...

Estimating fractal dimension of natural terrain from irregularly spaced data