Advances in Applied Probability · 1980 · 120 citations · 9 references
EngineeringBiostatisticsGeometryStochastic ProcessesUncertainty QuantificationMonte Carlo MethodsMonte Carlo SimulationPoint ProcessesSimulation MethodsRandom Sets
Let n points in the plane be generated by some specified random mechanism and suppose that N (∊) of the resulting triads form triangles with largest angle ≧ π – ∊. The main object of the paper is to obtain asymptotic formulae for and Var ( N (∊)) when ∊ ↓ 0, and to solve the associated data-analytic problem of testing whether an empirical set of n points should be considered to contain too many such ∊-blunt triads in the situation where the generating mechanism is unknown and where all that can be said about the tolerance ∊ is that it must be allowed to take values anywhere in a given interval ( T 0 , T 1 ) (0 < T 0 < T 1 ). This problem is solved by the introduction of a plot to be called the pontogram and by the introduction of simulation-based significance tests constructed by random lateral perturbations of the data.
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David G. Kendall · Advances in Applied Probability · 1977 · 483 citations
Finding the edge of a Poisson forest
B. D. Ripley, J.P. Rasson · Journal of Applied Probability · 1977 · 112 citations