PtProcess

R package PtProcess: Time Dependent Point Process Modelling. Fits and analyses time dependent marked point process models with an emphasis on earthquake modelling. For a more detailed introduction to the package, see the topic ”PtProcess”. A list of recent changes can be found in the topic ”Change Log”.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 10 articles , 1 standard article )

Showing results 1 to 10 of 10.
Sorted by year (citations)

  1. Sally Sun, Owen G. Ward, Jing Wu, Lihao Xiao, Xiaoxi Zhao, Tian Zheng: ppdiag: Diagnostic Tools for Temporal Point Processes (2021) not zbMATH
  2. Ushio Tanaka, Masami Saga, Junji Nakano: NScluster: An R Package for Maximum Palm Likelihood Estimation for Cluster Point Process Models Using OpenMP (2021) not zbMATH
  3. Abdollah Jalilian: ETAS: An R Package for Fitting the Space-Time ETAS Model to Earthquake Data (2019) not zbMATH
  4. Mancini, Luca; Paganoni, Anna Maria: Marked point process models for the admissions of heart failure patients (2019)
  5. Schoenberg, Frederic Paik; Hoffmann, Marc; Harrigan, Ryan J.: A recursive point process model for infectious diseases (2019)
  6. Kallah-Dagadu, G.; Nkansah, B. K.; Howard, N. K.: Flexible statistical modelling of the occurrences of transcription factor binding sites along a DNA sequence (2018)
  7. Meyer, Sebastian: Self-exciting point processes: infections and implementations (2018)
  8. Edzer Pebesma; Roger Bivand; Paulo Ribeiro: Software for Spatial Statistics (2015) not zbMATH
  9. Zhang, Tonglin: A Kolmogorov-Smirnov type test for independence between marks and points of marked point processes (2014)
  10. David Harte: PtProcess: An R Package for Modelling Marked Point Processes Indexed by Time (2010) not zbMATH