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as.array(<ndp>)
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Retrieve NDP parameter samples in Array Form |
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as.matrix(<ndp>)
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Retrieve Parameter Samples in Matrix Form |
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assign_mode()
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Estimates Posterior Mode Cluster Assignment |
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bend()
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Estimate the distribution of (B)uilt (E)nvironment amenities via the (N)ested (D)irichlet Process |
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bendr-datasets
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Datasets for bendr examples |
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beta_measure()
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Beta base measure |
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beta_nd_nhpp_fit()
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Estimate the nonhomgogenous poisson process intensity function from grouped data |
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get_square_error()
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Calculates Error Distribution under square loss function |
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green_loss()
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Lau and Green posterior loss function |
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green_loss_known()
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Computes Green and Lau Loss function with known classification |
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green_loss_unknown()
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Computes Green and Lau loss function with unknown classification |
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groupvo()
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Retrieve Grouped Data Structure |
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measures
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Base Measures |
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nd_nhpp_fit()
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Estimate the nonhomgogenous poisson process intensity function from grouped data |
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nd_nhpp_fixed_fit()
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Estimate the nonhomgogenous poisson process intensity function from grouped data with fixed concentration parameters |
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nsamples(<ndp>)
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Methods for ndp objects |
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ndp()
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ndp objects |
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normal_measure()
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Normal Base Measure |
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plot(<ndp>)
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Plot method for ndp objects |
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plot_cluster_densities()
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Plots cluster intensity function densities |
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plot_global_density()
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Plots global density function |
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plot_pairs()
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plots pairwise probability clustering plot |
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print(<ndp>)
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Print method for ndp objects |
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rnhpp()
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Random nonhomogenous poisson process generator |
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square_error()
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Computes Square loss with unknown classification |
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summary(<ndp>) print(<summary.ndp>)
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Summary method for ndp objects |
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traceplot()
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Traceplots of various NDP-NHPP parameters |
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transform_distances()
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Transform Distances |