c(person(given = "Nikolaus", family = "Umlauf", role = c("aut", "cre"), email = "Nikolaus.Umlauf@uibk.ac.at",
comment = c(ORCID = "0000-0003-2160-9803")),
person(given = "Daniel", family = "Adler", role = "aut", email = "dadler1@gwdg.de"),
person(given = "Thomas", family = "Kneib", role = "aut", email = "tkneib@uni-goettingen.de"),
person(given = "Stefan", family = "Lang", role = "aut", email = "Stefan.Lang@uibk.ac.at"),
person(given = "Achim", family = "Zeileis", role = "aut", email = "Achim.Zeileis@R-project.org",
comment = c(ORCID = "0000-0003-0918-3766")))
Nikolaus Umlauf [aut, cre] (<https://orcid.org/0000-0003-2160-9803>),
Daniel Adler [aut],
Thomas Kneib [aut],
Stefan Lang [aut],
Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>)

Bayesian Melding of GPS and DR Path for Animal Tracking
Bayesian melding approach to combine the GPS observations and Dead-Reckoned path for an accurate animal's track, or equivalently, use the GPS observations to correct the Dead-Reckoned path. It can take the measurement errors in the GPS observations into account and provide uncertainty statement about the corrected path. The main calculation can be done by the BMAnimalTrack function.

c(person("Yang (Seagle)", "Liu", role=c("aut", "cre"), email="yang.liu@stat.ubc.ca"), person("Brian C.", "Battaile", role=c("ctb"), email="brian.battaile at gmail.com"))
Yang (Seagle) Liu [aut, cre],
Brian C. Battaile [ctb]

person(given = "Issei",
family = "Tsunoda",
role = c("aut", "cre"),
email = "tsunoda.issei1111@gmail.com")
knitr, readxl, openxlsx, xlsx, stats, graphics, tcltk,
grDevices, ggplot2, methods, rstantools, car, hexbin, MASS,
crayon, DiagrammeR

person(given = "Issei",family = "Tsunoda",email = "tsunoda.issei1111@gmail.com", role = c("aut", "cre") )
knitr, readxl, xlsx, stats, graphics, tcltk, grDevices,
ggplot2, methods, car, crayon, DiagrammeR
rmarkdown, rstantools, openxlsx, hexbin, MASS

knitr, readxl, xlsx, stats, graphics, tcltk, grDevices,
ggplot2, methods, car, crayon, DiagrammeR, bridgesampling
'Close_all_graphic_devices.R' 'ConfirmConvergence.R'
'DrawCurves.R' 'DrawCurves_MRMC.R' 'DrawCurves_MRMC_pairwise.R'
'DrawCurves_MRMC_pairwise_BlackWhite.R'
'DrawCurves_MRMC_pairwise_col.R' 'DrawCurves_srsc.R'
'Draw_an_area_of_AUC_for_srsc.R' 'Make_TeX_file_for_summary.R'
'Replicate_MRMC_data.R' 'Rprofile.R'
'Simulation_Based_Calibration.R' 'StatisticForANOVA.R'
'Test_Null_Hypothesis_that_all_modalities_are_same.R'
'apply_foo.R' 'check_rhat.R' 'clearWorkspace.R' 'color.R'
'convertFromJafroc.R' 'create_dataset.R' 'dark_theme.R'
'dataset_creator_new_version.R' 'demo_Bayesian_FROC.R'
'demo_Bayesian_FROC_without_pause.R' 'document_dataset.R'
'document_dataset_MRMC.R' 'draw_bi_normal.R'
'explanation_about_package_BayesianFROC.R'
'explanation_for_what_curves_are_drawn.R' 'extractAUC.R'
'extract_EAP_CI.R' 'extract_EAP_by_array.R'
'extract_estimates_MRMC.R' 'fffaaabbb.R' 'fit_Bayesian_FROC.R'
'fit_MRMC_test.R' 'fit_MRMC_versionTWO.R'
'fit_Null_hypothesis_model_to_.R' 'fit_srsc.R'
'fit_srsc_per_image_test.R' 'fit_srsc_per_lesion.R'
'foo_of_a_List_of_Arrays.R' 'give_name_srsc_data.R'
'initial_values_specification_for_stan_in_case_of_MRMC.R'
'install_imports.R' 'layout.R' 'metadata_srsc_per_image.R'
'metadata_to_DrawCurve_MRMC.R' 'metadata_to_fit_MRMC.R'
'stanfitExtended.R' 'methods.R' 'methods_print.R'
'modelComparison.R'
'p_value_of_the_Bayesian_sense_for_chi_square_goodness_of_fit.R'
'packageStartupMessage.R'
'pairs_plot_if_divergent_transition_occurred.R' 'pause.R'
'plotFROC.R' 'showGraphicalModel.R' 'size_of_return_value.R'
'snippet_for_BayesianFROC.R' 'specify_priors.R'
'summarise_MRMC.R' 'summary_AUC_comparison_MRMC.R'
'summary_AUC_comparison_MRMC_with_crayon.R'
'summary_AUC_comparison_MRMC_without_crayon.R'
'summary_EAP_CI_srsc.R' 'the_row_number_of_logical_vector.R'
'validation.R' 'validation_MRMC.R' 'viewdata.R'
'viewdata_MRMC.R' 'viewdata_srsc.R' 'waic.R'