Statistical inference for spatial processes

By B. D. Ripley. 1990

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Citations in the corpus

Determinantal Point Processes for Machine Learning (2012, methodology): “The Gibbs point process provides such an approach, offering a general framework for incorporating correlations among selected items [Preston, 1976, Ripley and Kelly, 1977, Ripley, 1991, Van Lieshout, 2000, Møller and Waagepetersen, 2004, 2007, Daley and Vere-Jones, 2008].”
Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models (2004, background): “…for the MLE and related likelihood estimators under increasing-domain asymptotic for regression models with spatially correlated disturbances.3 Ripley (1988) pointed out that for fixed-domain asymptotic, as interactions will increase with observations, there is no theoretical basis for the…”
spatstat: An R Package for Analyzing Spatial Point Patterns (2005, methodology): “…spatial point patterns (e.g. Bartlett (1975); Cliﬀ and Ord (1981); Cressie (1991); Diggle (2003); van Lieshout (2000); Mat´ern (1986); Møller and Waagepetersen (2003); Moore (2001); Ripley (1981, 1988); Stoyan, Kendall, and Mecke (1995); Stoyan and Stoyan (1995); Upton and Fingleton (1985)).”
Fractals and spatial statistics of point patterns (2013, unknown): “Mathematical statisticians (Baddeley and Turner, 2012; Baddeley et al., 2008; Baddeley, 2007; Cressie, 2001; Rowlingson and Diggle, 1993, 1991; Ripley, 1988, 1981, 1976; Diggle, 1983) have developed very precise methods to estimate the parameters of constant-density point processes.”
A rigorous framework for optimization of expensive functions by surrogates (1998, background): “[30], it has been defended by others as a crude form of cross-validation [19, 10].”
A Studentized Permutation Test for the Comparison of Spatial Point Patterns (2012, methodology): “According to asymptotic results of Ripley (1984, 1988) for a Poisson point process of intensity λ, the variance can be approximated by var K̂(r) ≈ 2πr 2 λ2A(B) ( 1 + c1 U (B) A(B) r + c2 U (B) A(B) λr3 ) , (2) for small r, where U (B) stands for the perimeter of B.”
Analysis of long-term dynamics of crowns of sessile oaks at the stand level by means of spatial statistics (2008, methodology): “Ripley’s isotropic correction (Ohser, 1983; Ripley, 1988) was used for edge correction.”
Red-shifts and red herrings in geographical ecology (2000, background): “The other main route towards satisfactory treatment of spatial autocorrelation is that of parametric modelling which explicitly takes it into account (Ripley 1988, Haining 1990 and references therein).”
Data Clustering (2008, unknown): “The eld of spatial analysis of point patterns [153] is also related to cluster analysis.”
Philosophy and the practice of Bayesian statistics (2010, unknown): “The reasoning is the same: a model is a story of how the data could have been generated; the fitted model should therefore be able to generate synthetic data that look like the real data; failures to do so in important ways indicate faults in the model.”
Residual analysis for spatial point processes (with discussion) (2005, methodology): “However, heterogeneity and clustering are often confounded or unidentifiable [13, 14, 89, 91].”