Package: conmat 0.0.2.9000
conmat: Builds contact matrices using GAMs and population data
Builds contact matrices using GAMs and population data. This package incorporates data that is copyright Commonwealth of Australia (Australian Electoral Commission and Australian Bureau of Statistics) 2020.
Authors:
conmat_0.0.2.9000.tar.gz
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conmat.pdf |conmat.html✨
conmat/json (API)
NEWS
# Install 'conmat' in R: |
install.packages('conmat', repos = c('https://idem-lab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/idem-lab/conmat/issues
- abs_avg_school - ABS education data for 2016
- abs_avg_work - ABS work data for 2016
- abs_education_state - ABS education by state for 2006-2020
- abs_education_state_2020 - 2020 ABS education population data, interpolated into 1 year bins, by state.
- abs_employ_age_lga - ABS employment by age and LGA for 2016
- abs_household_lga - ABS household data for 2016
- abs_lga_lookup - ABS lookup table of states, lga code and lga name
- abs_pop_age_lga_2016 - ABS population by age for 2016 for LGAs
- abs_pop_age_lga_2020 - ABS population by age for 2020 for LGAs
- abs_state_age - ABS state population data for 2020
- age_group_lookup - Lookup table of age groups in 5 year bins
- conmat_original_school_demographics - Original school demographics for conmat
- conmat_original_work_demographics - Original work demographics for conmat
- data_abs_lga_education - LGA wise ABS education population data on different ages for year 2016
- data_abs_lga_work - LGA wise ABS work population data on different ages for year 2016
- data_abs_state_education - State wise ABS education population data on different ages for year 2016
- data_abs_state_work - State wise ABS work population data on different ages for year 2016
- davies_age_extended - Susceptibility and clinical fraction parameters from Davies et al.
- eyre_transmission_probabilities - Transmission probabilities of COVID19 from Eyre et al.
- polymod - Social contact data from 8 European countries
- polymod_setting_models - Polymod Settings models
- prem_germany_contact_matrices - Contact matrices as calculated by Prem. et al.
- setting_weights - Setting weights computed for transmission probabilities.
- vaccination_effect_example_data - Example dataset with information on age based vaccination coverage, acquisition and transmission
contact-matricesinfectious-diseasespopulation-datapublic-health
Last updated 3 months agofrom:86a8702ab6. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
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Doc / Vignettes | OK | Oct 25 2024 |
R-4.5-win | WARNING | Oct 25 2024 |
R-4.5-linux | WARNING | Oct 25 2024 |
R-4.4-win | WARNING | Oct 25 2024 |
R-4.4-mac | WARNING | Oct 25 2024 |
R-4.3-win | WARNING | Oct 25 2024 |
R-4.3-mac | WARNING | Oct 25 2024 |
Exports:%>%abs_abbreviate_statesabs_age_education_lgaabs_age_education_stateabs_age_lgaabs_age_stateabs_age_work_lgaabs_age_work_stateabs_unabbreviate_statesadd_age_partial_sumadd_intergenerationaladd_modelling_featuresadd_offsetadd_population_age_toadd_school_work_participationadd_symmetrical_featuresageage_breaksage_labelage_populationaggregate_predicted_contactsapply_vaccinationas_conmat_populationas_setting_prediction_matrixautoplotclean_term_namesconmat_populationcreate_age_gridestimate_setting_contactsextract_term_namesextrapolate_polymodfit_setting_contactsfit_single_contact_modelgenerate_ngmgenerate_ngm_ozget_abs_household_size_distributionget_abs_household_size_populationget_abs_per_capita_household_sizeget_abs_per_capita_household_size_lgaget_abs_per_capita_household_size_stateget_age_population_functionget_polymod_contact_dataget_polymod_per_capita_household_sizeget_polymod_populationget_polymod_setting_dataget_setting_transmission_matricesgg_age_partial_pred_longgg_age_partial_sumgg_age_terms_settingsmatrix_to_predictionsnew_age_matrixnew_ngm_setting_matrixnew_setting_dataper_capita_household_sizepivot_longer_age_predspolymodpopulationpopulation_labelpredict_contactspredict_contacts_1ypredict_individual_termspredict_setting_contactspredictions_to_matrixprepare_population_for_modellingraw_eigenvaluescalingsetting_prediction_matrixtransmission_probability_matrix
Dependencies:askpassbitbit64cachemclicliprcodetoolscolorspacecountrycodecpp11crayoncurldata.tablediffobjdigestdplyrenglishfansifarverfastmapfurrrfuturegenericsggplot2globalsgluegtablehmshttrisobandjsonlitelabelinglatticelifecyclelistenvlubridatemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeoaiopensslparallellypatchworkpillarpkgconfigplyrprettyunitsprogresspurrrR6RColorBrewerRcppreadrrematch2rlangscalessocialmixrstringistringrsystibbletidyrtidyselecttimechangetzdbutf8vctrsviridisLitevroomwaldowithrwpp2017xml2
Conmat Population Data
Rendered fromconmat-population.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-03-08
Started: 2022-12-23
Data Sources
Rendered fromdata-sources.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-01-17
Started: 2022-09-08
Example Pipeline
Rendered fromexample-pipeline.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-01-20
Started: 2022-09-08
Getting Started
Rendered fromgetting-started.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2024-06-20
Started: 2021-09-06
Parallel Computing
Rendered fromparallel-computing.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-02-09
Started: 2022-12-23
SIR modelling with conmat
Rendered fromsir-model.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-03-08
Started: 2023-02-07
Using other data sources
Rendered fromother-data-sources.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-03-08
Started: 2022-12-23
Visualisation gallery
Rendered fromvisualising-conmat.Rmd
usingknitr::rmarkdown
on Oct 25 2024.Last update: 2023-03-08
Started: 2022-12-23