Combining herbarium data with spatial data: potential benefits, new needs

Combining Incompatible Spatial Data

Global positioning systems (GPSs) and geographical information systems (GISs) have been widely used to collect and synthesize spatial data from a variety of sources. New advances in satellite imagery and remote sensing now permit scientists to access spatial data at several different resolutions. The Internet facilitates fast and easy data acquisition. In any one study, several different types ...

New DEA/Location Models with Interval Data

Recently the concept of facility efficiency, which defined by data envelopment analysis (DEA), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. By combining the DEA models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

Bayesian Analysis of Survival Data with Spatial Correlation

Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox...

Bayesian Prediction in Spatial Data Analysis

Combining time DEA scores using a dynamic panel data model

We define a combined DEA score to evaluate efficiency in agricultural research. The production model we propose considers efficiency measurements under variable returns to scale for each year in the period 2012–2017. We postulate a first-order autoregressive process in the presence of covariates, to explain efficiency. Powers of the autocorrelation coefficient estimated assuming a dynamic panel...