[Openspace] Virtual Registration Added for "Advances in Spatial Regression Analysis"

[Julia Koschinsky]

Dear all,

We received a lot of requests to open our January 12-15 workshop for
virtual registration. To meet this interest, we will offer the option
to participate virtually in the course (you will need a fast internet
connection and web browser):

COST: $1,200
CONTENT: Lecture and lab the same as in-person participation. However,
virtual participation is one-way only (listen to the lectures and lab
demos). In contrast to in-person participation, virtual participants
will not be able to ask questions or get lab assistance (including
with software use, questions about research projects, or data setup),
or schedule office hours with Dr. Anselin.

We will add the registration and payment option for virtual
participation in the next days
(http://geodacenter.asu.edu/learning/workshops). Please contact me at
julia.koschinsky at asu.edu if you need to register before then or have
any other questions.

With best regards,
Julia


---------- Forwarded message ----------
From: Julia Koschinsky <jkoschin at asu.edu>
Date: 2008/9/24
Subject: "Advances in Spatial Regression Analysis" with Luc Anselin in Jan. 2009
To: openspace at sal.uiuc.edu


Dear all,

In response to repeated requests, the GeoDa Center for Geospatial
Analysis and Computation at Arizona State University is announcing a
four-day workshop "Advances in Spatial Regression Analysis" with Luc
Anselin. We are also planning subsequent workshops on computational
techniques for spatial analysis and econometrics (Python and R).

The workshop site with additional information and registration/payment
options will be available shortly. If you prefer to register/pay for
the workshop before October 1 or have other questions, please contact
me at julia.koschinsky at asu.edu.

DATE: January 12-15, 2009
LOCATION: Arizona State University in Tempe, AZ (Phoenix metro area, USA)
INSTRUCTOR: Dr. Luc Anselin, Director, GeoDa Center for Geospatial
Analysis and Computation, Arizona State University
COST: $1,500 (credit card only, first-come, first served)

AUDIENCE: Aimed at users with a solid background in the principles and
methods of regression analysis and intermediate familiarity with
spatial regression. This course approaches the material at the level
of an intermediate graduate econometrics or statistics course. The
focus is on spatial regression in a cross-sectional setting. This is
not an introductory course.

WORKSHOP CONTENT:
Day 1: Spatial autocorrelation refresher, spatial weights,
non-traditional spatial weights, semi-parametric approaches in spatial
econometrics, including different ways to introduce semi-parametrics
into spatial models, and non-parametric spatial covariance estimation.

Days 2-4: Maximum Likelihood (ML) and General Method of Moments (GMM)
approaches in spatial econometrics, including Lagrange Multiplier
tests, ML estimation, optimal GMM, models for both heteroskedasticity
and spatial error dependence and heteroskedastic and autocorrelation
consistent (HAC) variance estimators
--Day 2: Model Specification and Specification Tests
--Day 3: Estimation, Part 1
--Day 4: Estimation, Part 2

Lectures and demonstrations will be held in the morning session, while
in the afternoon the emphasis will be on hands on experience and
laboratory exercises using cutting edge specialized software,
including the brand new PySpace and OpenGeoDa packages developed at
the GeoDa Center, as well as the R spdep package. There will also be
an opportunity to discuss individual research problems with Dr.
Anselin in "office hours."

We look forward to seeing you in Phoenix,
Julia

************************
Julia Koschinsky, Ph.D.
Research Director
Arizona State University
GeoDa Center for Geospatial Analysis and Computation
URL: http://geodacenter.asu.edu
Email: julia.koschinsky at asu.edu



-- 
************************
Julia Koschinsky, Ph.D.
Research Director
Arizona State University
GeoDa Center for Geospatial Analysis and Computation
URL: http://geodacenter.asu.edu
Email: julia.koschinsky at asu.edu