A method for estimating and simulating the distribution of spatial point events based on B-spline
smoothing, comprising: collecting independently recorded spatial
point location data corresponding to a number of spatial location nodes; selecting the
least squares estimator or maximum likelihood estimator using B-spline
smoothing according to the number of samples, and obtaining the optimal
coefficient matrix by solving the corresponding
optimization problem; calculating the
intensity function using the obtained optimal
coefficient matrix estimate, and applying the
Thinning algorithm to generate
pseudo data for simulating the distribution of spatial point events, which are further used in Monte Carlo
simulation to infer the expected value of spatial statistics. The method exhibits significant flexibility, smoothness and robustness when
processing spatial data, effectively reduces the
impact of
noise data, and improves the accuracy and reliability of the model. Through experimental
verification, the present invention is superior to the traditional
kernel method in multiple evaluation indicators, and provides a new and efficient solution for the
estimation and
simulation of spatial
point event distribution.