Simulating Nonhomogeneous Poisson Point Processes

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Documentation for package ‘nhppp’ version 0.1.4

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check_ppp_sample_validity Check the validity of ppp samples
check_ppp_vector_validity Check the validity of a ppp vector.
compare_ppp_vectors Check that two ppp vectors Q-Q agree
draw Generic function for simulating from NHPPPs given the intensity function or the cumulative intensity function.
draw_cumulative_intensity_inversion Simulate from a non homogeneous Poisson Point Process (NHPPP) from (t_min, t_max) (inversion method)
draw_cumulative_intensity_orderstats Simulate from a non homogeneous Poisson Point Process (NHPPP) from (t_min, t_max) (order statistics method)
draw_intensity Simulate from a non homogeneous Poisson Point Process (NHPPP) from (t0, t_max) (thinning method)
draw_intensity_step Simulate from a non homogeneous Poisson Point Process (NHPPP) from (t0, t_max) (thinning method) with piecewise constant_majorizer
draw_sc_linear Special case: Simulate from a non homogeneous Poisson Point Process (NHPPP) from (t_min, t_max) with linear intensity function (inversion method)
draw_sc_loglinear Special case: Simulate from a non homogeneous Poisson Point Process (NHPPP) from (t_min, t_max) with log-linear intensity function (inversion method)
draw_sc_step Simulate a piecewise constant-rate Poisson Point Process over (t_min, t_max] (inversion method) The intervals need not have the same length.
draw_sc_step_regular Sampling from NHPPPs with piecewise constant intensities with same interval lengths (non-vectorized)
expect_no_error Helper functions
get_step_majorizer Piecewise constant (step) majorizer for K-Lipschitz functions over an interval (vectorized over the 'breaks' argument).
inverse_with_uniroot Numerically evaluate the inverse of a function at a specific point
inverse_with_uniroot_sorted Numerically evaluate the inverse of a monotonically increasing continuous function from R to R at specific points.
Lambda_exp_form Definite integral of 'l = exp(alpha + beta*t)' at time 't' with 'L(t0) = 0'
Lambda_inv_exp_form Inverse of the definite integral of 'l = exp(alpha + beta*t)' at time 't'
Lambda_inv_linear_form Inverse of the definite integral of 'l = alpha + beta*t' at time 't'
Lambda_linear_form Definite integral of 'l = alpha + beta*t' at time 't' with 'L(t0) = 0'
make_cumulative_Lambda_matrix Helper function for the vectorized versions of sampling functions. Takes the usual ways that 'lambda_mat' and 'Lambda_mat' are specified and returns 'Lambda_mat'.
make_lambda_matrix Helper function for the vectorized versions of sampling functions. Takes the usual ways that 'lambda_mat' and 'Lambda_mat' are specified and returns 'lambda_mat'.
make_range_t_matrix Helper function for the vectorized versions of sampling functions. Takes the usual ways that 'range_t' is specified (a 2-vector, a 1 x 2 or an r x 2 matrix) and returns a r x 2 matrix.
mat_cumsum_columns Return matrix with column-wise cumulative sum No checks for arguments is done.
mat_cumsum_columns_with_scalar_ceiling Return matrix with column-wise cumulative sum replacing cells larger than 'ceil' with 'NA'. No checks for arguments is done.
mat_cumsum_columns_with_vector_ceiling Return matrix with column-wise cumulative sum replacing cells larger than 'ceil' with 'NA'. No checks for arguments is done.
mat_diff_columns Return matrix with column-wise differencing. No checks for arguments is done.
ppp_n Simulate specific number of points from a homogeneous Poisson Point Process over (t_min, t_max]
ppp_next_n Simulate n events from a homogeneous Poisson Point Process.
ppp_orderstat Simulate a homogeneous Poisson Point Process over (t_min, t_max] (order statistics method)
ppp_sequential Simulate a homogeneous Poisson Point Process over (t_min, t_max]
read_code Read code from text file as string
rng_stream_rexp Exponential random samples from 'rstream' objects
rng_stream_rpois Poisson random samples from 'rstream' objects
rng_stream_runif Uniform random samples from 'rstream' objects
rng_stream_rztpois Zero-truncated Poisson random samples from 'rstream' objects
rztpois Zero-truncated Poisson random samples (basic R)
simpson_num_integr Simpson's method to integrate a univariate function.
vdraw Vectorized generic function for simulating from NHPPPs given the intensity function or the cumulative intensity function
vdraw_intensity_step_regular Vectorized sampling from a non homogeneous Poisson Point Process (NHPPP) from an interval (thinning method) with piecewise constant_majorizers (C++)
vdraw_intensity_step_regular_cpp Vectorized sampling from a non homogeneous Poisson Point Process (NHPPP) from an interval (thinning method) with piecewise constant_majorizers (C++)
vdraw_intensity_step_regular_R Vectorized sampling from a non homogeneous Poisson Point Process (NHPPP) from an interval (thinning method) with piecewise constant_majorizers (R)
vdraw_sc_step_regular Vectorized sampling from NHPPPs with piecewise constant intensities with same interval lengths (R)
vdraw_sc_step_regular_cpp Vectorized sampling from NHPPPs with piecewise constant intensities with same interval lengths (C++)
vdraw_sc_step_regular_R Vectorized sampling from NHPPPs with piecewise constant intensities with same interval lengths (R)
vztdraw_intensity_step_regular Vectorized sampling from a zero-truncated non homogeneous Poisson Point Process (NHPPP) from an interval (thinning method) with piecewise constant_majorizers
vztdraw_intensity_step_regular_R Vectorized sampling from a zero-truncated non homogeneous Poisson Point Process (NHPPP) from an interval (thinning method) with piecewise constant_majorizers (R)
vztdraw_sc_step_regular Vectorized sampling from zero-truncated NHPPPs with piecewise constant intensities with same interval lengths
vztdraw_sc_step_regular_cpp Vectorized sampling from zero-truncated NHPPPs with piecewise constant intensities with same interval lengths (C++)
vztdraw_sc_step_regular_R Vectorized sampling from zero-truncated NHPPPs with piecewise constant intensities with same interval lengths (R)
ztdraw_cumulative_intensity Simulate from a zero-truncated non homogeneous Poisson Point Process (zt-NHPPP) from (t_min, t_max) (order statistics method)
ztdraw_intensity Simulate 'size' samples from a zero-truncated non homogeneous Poisson Point Process (zt-NHPPP) from (t0, t_max) (thinning method)
ztdraw_intensity_step Simulate from a zero-truncated non homogeneous Poisson Point Process (NHPPP) from (t0, t_max) (thinning method) with piecewise constant_majorizer
ztdraw_sc_linear Simulate 'size' samples from a zero-truncated non homogeneous Poisson Point Process (zt-NHPPP) from (t_min, t_max) with linear intensity function
ztdraw_sc_loglinear Simulate from a zero-truncated non homogeneous Poisson Point Process (zt-NHPPP) from (t_min, t_max) with a log-linear intensity function (inversion method)
ztppp Simulate a zero-truncated homogeneous Poisson Point Process over (t_min, t_max]