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Astrophysics Source Code Library

Making codes discoverable since 1999

Searching for codes credited to 'Robert, P.'

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Found 3 codes.

[ascl:2405.001] SPEDAS: Space Physics Environment Data Analysis System
Angelopoulos, V.; Cruce, P.; Drozdov, A.; Grimes, E. W.; Hatzigeorgiu, N.; King, D. A.; Larson, D.; Lewis, J. W.; McTiernan, J. M.; Roberts, D. A.; Russell, C. L.; Hori, T.; Kasahara, Y.; Kumamoto, A.; Matsuoka, A.; Miyashita, Y.; Miyoshi, Y.; Shinohara, I.; Teramoto, M.; Faden, J. B.; Halford, A. J.; McCarthy, M.; Millan, R. M.; Sample, J. G.; Smith, D. M.; Woodger, L. A.; Masson, A.; Narock, A. A.; Asamura, K.; Chang, T. F.; Chiang, C. Y.; Kazama, Y.; Keika, K.; Matsuda, S.; Segawa, T.; Seki, K.; Shoji, M.; Tam, S. W. Y.; Umemura, N.; Wang, B. J.; Wang, S. Y.; Redmon, R.; Rodriguez, J. V.; Singer, H. J.; Vandegriff, J.; Abe, S.; Nose, M.; Shinbori, A.; Tanaka, Y. M.; UeNo, S.; Andersson, L.; Dunn, P.; Fowler, C.; Halekas, J. S.; Hara, T.; Harada, Y.; Lee, C. O.; Lillis, R.; Mitchell, D. L.; Argall, M. R.; Bromund, K.; Burch, J. L.; Cohen, I. J.; Galloy, M.; Giles, B.; Jaynes, A. N.; Le Contel, O.; Oka, M.; Phan, T. D.; Walsh, B. M.; Westlake, J.; Wilder, F. D.; Bale, S. D.; Livi, R.; Pulupa, M.; Whittlesey, P.; DeWolfe, A.; Harter, B.; Lucas, E.; Auster, U.; Bonnell, J. W.; Cully, C. M.; Donovan, E.; Ergun, R. E.; Frey, H. U.; Jackel, B.; Keiling, A.; Korth, H.; McFadden, J. P.; Nishimura, Y.; Plaschke, F.; Robert, P.; Turner, D. L.; Weygand, J. M.; Candey, R. M.; Johnson, R. C.; Kovalick, T.; Liu, M. H.; McGuire, R. E.; Breneman, A.; Kersten, K.; Schroeder, P.
The SPEDAS (Space Physics Environment Data Analysis Software) framework supports multi-mission data ingestion, analysis and visualization for the Space Physics community. It standardizes the retrieval of data from distributed repositories, the scientific processing with a powerful set of legacy routines, the quick visualization with full output control and the graph creation for use in papers and presentations. SPEDAS includes a GUI for ease of use by novice users, works on multiple platforms, and though based on IDL, can be used with or without an IDL license. The framework supports plugin modules for multiple projects such as THEMIS, MMS, and WIND, and provides interfaces for software modules developed by the individual teams of those missions. A Python implementation of the framework, PySPEDAS (ascl:2405.005), is also available.
[ascl:2211.008] pmclib: Population Monte Carlo library
Benabed, Karim; Cappé, Olivier; Cardoso, Jean-François; Fort, Gersende; Kilbinger, Martin; Prunet, Simon; Robert, Christian P.; Wraith, Darren
The Population Monte-Carlo (PMC) sampling code pmclib performs fast end efficient parallel iterative importance sampling to compute integrals over the posterior including the Bayesian evidence.
[ascl:1212.006] CosmoPMC: Cosmology sampling with Population Monte Carlo
Kilbinger, Martin; Benabed, Karim; Cappé, Olivier; Coupon, Jean; Cardoso, Jean-François; Fort, Gersende; McCracken, Henry Joy; Prunet, Simon; Robert, Christian P.; Wraith, Darren
CosmoPMC is a Monte-Carlo sampling method to explore the likelihood of various cosmological probes. The sampling engine is implemented with the package pmclib. It is called Population MonteCarlo (PMC), which is a novel technique to sample from the posterior. PMC is an adaptive importance sampling method which iteratively improves the proposal to approximate the posterior. This code has been introduced, tested and applied to various cosmology data sets.