Loading…
This event has ended. Visit the official site or create your own event on Sched.
Click here to return to main conference site. For a one page, printable overview of the schedule, see this.
View analytic
Wednesday, June 29 • 1:18pm - 1:36pm
SpatialProbit for fast and accurate spatial probit estimations

Log in to save this to your schedule and see who's attending!

This package meets the emerging needs of powerful and reliable models for the analysis of spatial discrete choice data. Since the explosion of available and voluminous geospatial and location data, existing estimation techniques cannot withstand the course of dimensionality and are restricted to samples counting having less than a few thousand observations.
The functions contained in SpatialProbit allow fast and accurate estimations of Spatial Autoregressive and Spatial Error Models under Probit specification. They are based on the full maximization of likelihood of an approximate multivariate normal distribution function, a task that was considered as prodigious just seven years ago (Wang et al. 2009). Extensive simulation and empirical studies proved that these functions can readily handle sample sizes with as many as several millions of observations, provided the spatial weight matrix is in convenient sparse form, as is typically the case for large data sets, where each observation neighbours only a few other observations.
SpatialProbit relies amongst others on Rcpp, RcppEigen and Matrix packages to produce fast computations for large sparse matrixes.nnPossible applications of spatial binary choice models include spread of diseases and pathogens, plants distribution, technology and innovation adoption, deforestation, land use change, amongst many others.
We will present the results of the SpatialProbit package for a large database on land use change at the plot level.

Moderators
avatar for Edzer Pebesma

Edzer Pebesma

professor, University of Muenster
My research interested is spatial, temporal, and spatiotemporal data in R. I am one of the authors, and maintainer, of sp. You'll find my tutorial material at https://edzer.github.io/UseR2016/ - note that I may update it until shortly before the tutorial.

Speakers
avatar for Davide  Martinetti

Davide Martinetti

Post-Doc, INRA PACA


Wednesday June 29, 2016 1:18pm - 1:36pm
SIEPR 120 366 Galvez St, Stanford, CA 94305

Attendees (38)