The Saddlepoint Approximation of Moran's I's and Local Moran's I i's Reference Distributions and Their Numerical Evaluation

By Michael Tiefelsdorf. 2002

125 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a81c15903fa73e3efae334e07aa71b1ed0952934

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Daniel A. Griffith
2. Roger S. Bivand
3. Michael Tiefelsdorf
4. Eleonora Patacchini
5. Yves Zenou
6. David W. S. Wong
7. Luc Anselin
8. Yongwan Chun

Citations in the corpus

• Spatial Dependence in Local Unemployment Rates (2007, background): “13This choice is grounded on the fact that it is now common knowledge that the reference distribution of the local Moran’s I statistic deviates substantially from the normal distribution (see, e.g., Tiefelsdorf, 2002).”
• Comparing implementations of global and local indicators of spatial association (2018, methodology): “2.1.1 (Tiefelsdorf 2002; Bivand et al. 2009).”
• Semiparametric Filtering of Spatial Autocorrelation: The Eigenvector Approach (2007, methodology): “Under global spatial independence of the regression residuals, which is induced after successfully completing the spatial filtering procedure, the calculation of the significance points of local Moran's Ii is simplified and the saddlepoint approximation (6) (Tiefelsdorf, 2002) can be directly used.”