R: Tests of Independence and Analysis of Dependence Between Point Processes in Time

# Tests of Independence and Analysis of Dependence Between Point Processes in Time

## Documentation for package ‘IndTestPP’ version 3.0

- DESCRIPTION file

## Help Pages

IndTestPP-package | Tests of Independence and Analysis of Dependence between Point Processes in Time
BinPer | Percentage of concordant intervals
buscar | Generating points in a Poisson process
calcdist | Calculates the set of close points and the mean distance in a vector of processes, for each point in the first process
calcNmu | Conditional test of independence between two Poisson process
ComplPos | Changes format of the vector of occurrence times in a point process
CondTest | Conditional test of independence between two Poisson process
CountingCor | Correlation between the counting variables in two point processes
countP | Correlation between the counting variables in two point processes
CPSPpoints | Identifying the occurrence points of the indicator processes in a CPSP
CPSPPOTevents | Identifying the occurrence points of the indicator processes in the CPSP from a POT approach
depchi | Estimating extremal dependence coefficientes
DepCPSPKenv | Estimating cross K-function and envelopes for marginal processes of a CPSP
DepCPSPNHK | Estimating cross K-function and envelopes for marginal processes of a CPSP
DepNHCPSP | Generating a Common Poisson Shock Process
DepNHNeyScot | Generating a multivariate Neyman-Scott cluster process
DepNHPPMarked | Generating dependent point processes from a marked Poison Process
DepNHPPqueue | Generating dependent point processes by a tandem queueing network
DepNHPPqueue1 | Generating dependent point processes by a tandem queueing network
DepNHPPqueueI | Generating dependent point processes by a tandem queueing network
DepqueueKenv | Estimating cross K-function and envelopes for the marginal processes of a queue
DepqueueNHK | Estimating cross K-function and envelopes for the marginal processes of a queue
DistObs | Calculates the set of close points and the mean distance in a vector of processes, for each point in the first process
DistShift | Generates by translation a vector of independent processes, and calculates the set of close points and the mean distance for each point in the first process
DistSim | Generates a vector of independent processes, and calculates the set of close points and the mean distance for each point in the first process
DistSimfix | Generates a vector of independent processes, and calculates the set of close points and the mean distance for each point in the first process
DutilleulPlot | A graphical test to assess independence between two point processes
firstt | Simulated intervals in a vector of point processes
fn2 | Parametric bootstrap test of independence between point processes
fn2B | Lotwick-Silverman test of independence between point processes
fn2fix | Parametric bootstrap test of independence between point processes
fn3 | A graphical test to assess independence between two point processes
funMPPGen | Simulated intervals in a vector of point processes
genbiPos | Calculating the set of close points
GenSons | Generating a multivariate Neyman-Scott cluster process
gentriPos | Calculating the set of close points
HDFaux | Estimating the D-function
IndNHNeyScot | Generating a vector of independent Neyman-Scott cluster processes
IndNHPP | Generates trajectories of independent Poisson processes
IndTestPP | Tests of Independence and Analysis of Dependence between Point Processes in Time
IntMPP | Simulated intervals in a vector of point processes
Jenv | Estimating the cross J-function and testing independence
Kenv | Estimating cross K-function and testing independence
marca | Identifying the occurrence points of the indicator processes in a CPSP
miKS | Parametric bootstrap test of independence between point processes
mirank | Parametric bootstrap test of independence between point processes
nearestD | Estimating the D-function
nearestdist | Distance to the nearest point
NHD | Estimating the D-function
NHDaux | Estimating the D-function
NHDFaux | Estimating the cross J-function and testing independence
NHF | Estimating the F-function
NHFaux | Estimating the F-function
NHJ | Estimating the cross J-function and testing independence
NHJaux | Estimating the cross J-function and testing independence
NHK | Estimating cross K-function and testing independence
NHKaux | Estimating cross K-function and testing independence
NHKaux2 | Estimating cross K-function and testing independence
NHKaux3 | Estimating cross K-function and testing independence
nMenr | Estimating the D-function
NumI | Simulated intervals in a vector of point processes
pdist | Distance to the nearest point
PlotICPSP | Plotting the occurrence points of the indicator processes in a CPSP
PlotMargP | Plotting the occurrence points of a vector of point processes
PlotMCPSP | Plotting the occurrence points of the marginal processes in a CPSP
prodN2 | Estimating the D-function
PsimNHPc | Generating a Common Poisson Shock Process
simHPc | Generating points in a homogenous Poisson process
simNHPc | Generating points in a Poisson process
SpecGap | Stationary distribution of a matrix and its spectral gap
TestIndLS | Lotwick-Silverman test of independence between point processes
TestIndNH | Parametric bootstrap test of independence between point processes
TranM | Estimation of the transition matrix of a Markov chain
TxBHZ | Daily maximum temperature at Barcelona, Huesca and Zaragoza
uniongentri | Calculating the set of close points