Bidimensional regression: Issues with interpolation

Tyler Thrash, Ioannis Giannopoulos, Victor R Schinazi

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review


We investigated the interpolation of missing values in data that were fit by bidimensional regression models. This addresses a problem in spatial cognition research in which sketch maps are used to assess the veracity of spatial representations. In several simulations, we compared samples of different sizes with different numbers of interpolated coordinate pairs. A genetic algorithm was used in order to estimate parameter values. We found that artificial inflation in the fit of bidimensional regression models increased with the percent of interpolated coordinate pairs. Furthermore, samples with fewer coordinate pairs resulted in more inflation than samples with more coordinate pairs. These results have important implications for statistical models, especially those applied to the analysis of spatial data.
Original languageEnglish
Title of host publicationCogSci 2014 - Proceedings of the 36th Annual Conference of the Cognitive Science Society
Subtitle of host publicationCognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts
Place of PublicationAustin
PublisherCognitive Science Society
Number of pages6
ISBN (Electronic)978-0-9911967-0-8, 978-1-63439-116-0
Publication statusPublished - 2014
Externally publishedYes
Event36th Annual Meeting of the Cognitive Science Society: Cognitive Science Meets Artificial Intelligence: Human and Artificial Agents in Interactive Contexts - Quebec, Canada
Duration: 23 Jul 201426 Jul 2014
Conference number: 36th


Conference36th Annual Meeting of the Cognitive Science Society
Abbreviated titleCogSci 2014
Internet address


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