Test for Spatio-Temporal Counts Being Poisson

Test for Spatio-Temporal Counts Being Poisson

A test for stationarity for spatio-temporal data

Many random phenomena in the environmental and geophysical sciences are functions of both space and time; these are usually called spatio-temporal processes. Typically, the spatio-temporal process is observed over discrete equidistant time and at irregularly spaced locations in space. One important aim is to develop statistical models based on what is observed. While doing so a commonly used as...

Observation Driven Models for Poisson Counts

This paper is concerned with a general class of observation driven models for time series of counts whose conditional distributions given past observations and explanatory variables follow a Poisson distribution. These models provide a flexible framework for modeling a wide range of dependence structures. Conditions for stationarity and ergodicity of these processes are established from which t...

Modeling and Anomaly Detection for Event Occurrences Following an Inhomogeneous Spatio-Temporal Poisson Process

This paper presents a model that describes spatial variations of the intensity of events that occur at random geographical locations. An inhomogeneous Poisson process is used to model the intensity over a spatial region with multiplicative spatial and temporal covariate effects. Dynamic temporal effects are incorporated into the model allowing changes in the intensity structure over time. Addit...

Modeling of spatio-temporal of albedo over Iran

The aim of this study is modeling spatiotemporal variations of albedo. This study was conducted using simultaneous effects of several components, such as wetness of surface layer of soil, cloudiness, topography and vegetation density (NDVI), using MEERA2 model with a resolution of 50 in 50 km during 2000-2010 in Iran. The results of spatial analysis of albedo values in Iran showed that the high...