I started this blog to post about research endeavors and interests of mine both professionally and academically. The purpose of this blog is 3-fold:
1) Demonstrate the relevance and spatial statistical power (and fun!) of the R programming language
2) Teach others with a background in research and statistics how to use these R features
3) Gain feedback on my work
With this site, I’m going to continue attempting to hammer on what is actually transpiring in R, ideally without dragging my feet and stagnating the more advanced users, using an intuitive approach so readers understand not just THAT something happens, but HOW and WHY it happens. This ideally means they remember, are able to reproduce results, and ultimately grow in their learning. Your feedback is key!
I’m available for hire on specific projects (modeling, report writing, data visualization) so please feel free to email me.
If you want to learn a little about me…
My name is Paul Bidanset. I am completing a PhD with the University of Ulster in real estate valuation modeling. I also work as a modeler and statistician for a local government in southeast Virginia. In this role, I am exploring spatial and temporal modeling approaches to increase equity and uniformity of ad valorem real estate property assessments. I graduated in 2009 with a B.S. in economics from James Madison University, and received an M.A. in economics from Old Dominion University in August of 2013. My research areas of interest include: geocomputation, quantitative geography, spatial analysis, spatiotemporal methods, and mass appraisal of real estate. In my spare time I play a mean clawhammer banjo, lounge with my Weimaraner Scout, and go barefoot in the great outdoors by any and all means possible (fishing, kayaking, camping, etc.)
Recent academic achievements:
• Bidanset, P. & Lombard, J. (2014). The effect of kernel and bandwidth specification ingeographically weighted regression models on the accuracy and uniformity of mass realestate appraisal. Journal of Property Tax Assessment & Administration. 11(3).
• Bidanset, P. & Lombard, J. (2014). Evaluating spatial model accuracy in mass real estate appraisal: A comparison of geographically weighted regression (GWR) and the spatial lag model (SLM). Cityscape: A Journal of Policy Development and Research. 16(3).
• Bidanset, P. E. (2014). Geographic data visualization and mapping in R: implications for empowering the assessment community with spatial analysis. Fair & Equitable, 12(3), 3-11.
• Bidanset, P E. (2014). Moving automated valuation models out of the box: the global geography of AVMs. Fair & Equitable, 12(7), 3-7.
Conference Papers & Presentations:
• Bidanset, P., McCluskey, B., & Davis, P. (2015, Jun 16-Jun 17). Response Surface Analysis: A Revisitation. International Property Tax Institute (IPTI) 2015 Mass Appraisal Valuation Symposium. Amsterdam, The Netherlands.
• Bidanset, P., Lombard, J., & Davis, P. (2015, Apr 15-18). Proximity Effects of Light Rail Transit on Property Values: A Spatial Evaluation of Walking Distances. American Real Estate Society (ARES) 2015 Annual Meeting. Fort Myers, FL.
• Bidanset, P., Lombard, J., & Davis, P. (2015, May 11-13). Proximity Effects of Light Rail Transit on Property Values: A Spatial Evaluation of Walking Distances. Applied Geography International Geographical Union (IGU) Conference 2015: Applied Service Analysis and Planning. Bangkok, Thailand.
• Bidanset, P. (2015, Mar 2-5). Using GIS & Spatial Modeling to Identify and Calibrate Sub-Geographic Appraisal Models. Paper to be presented at the International Association of Assessing Officers (IAAO) and Urban and Regional Information Systems Association (URISA) 19th GIS/CAMA Technologies Conference. Oklahoma City, OK.
• Bidanset, P. (2015, Mar 2-5). Geographic Data Visualization and Spatial Analysis with Open-Source Software: An Instructional Tutorial for Assessment Professionals. Paper to be presented at the International Association of Assessing Officers (IAAO) and Urban and Regional Information Systems Association (URISA) 19th GIS/CAMA Technologies Conference. Oklahoma City, OK.
• Bidanset, P. & Lombard, J. (2014, Nov 12-15). Evaluating Spatial Model Accuracy in Mass Real Estate Appraisal: A Comparison of Geographically Weighted Regression (GWR) and the Spatial Lag Model (SLM). North American Regional Science Council’s (NARSC) 61st Annual North American Meetings of the Regional Science Association International. Bethesda, MD.
• Bidanset, P. (2014, Jul 16-18). Empowering Assessors with GIS: Promoting the Assessment Process with Geographic Data Visualization and Spatial Modeling. Presented at the Virginia Association of Assessing Officers Annual Education Seminar. Charlottesville, VA.
• Bidanset, P. & Lombard, J. (2014, Feb 24-27). Learning more about geographically weighted regression: optimal spatial weighting functions used in mass appraisal of residential real estate. Paper presented at the International Association of Assessing Officers (IAAO) and Urban and Regional Information Systems Association (URISA) 18th GIS/CAMA Technologies Conference. Jacksonville, FL
• Bidanset, P. & Lombard, J. (2013, May 29-Jun 2). Optimal spatial weighting functions of geographically weighted regression models used in mass appraisal of residential real estate. Paper presented at the International Geographic Union (IGU) Conference 2013: Applied GIS and Spatial Modelling, Leeds, UK.
I am also helping contribute to several books and journals on spatial modeling which I will be happy to share once they have been published.
More of my professional and academic accomplishments can be found here.
All works on this site (spatioanalytics.com) are subject to copyright (all rights reserved) 2013-2015. All that is published is my own and does not represent my employers or affiliated institutions.