{ "_id": "6a101f7cacfb0bcc41c8b3b3", "Package": "conmat", "Title": "Builds Contact Matrices using Generalised Additive Models (GAMs)\nand Population Data", "Version": "0.1.0", "Authors@R": "c(\nperson(given = \"Nicholas\",\nfamily = \"Tierney\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"nicholas.tierney@gmail.com\",\ncomment = c(ORCID = \"0000-0003-1460-8722\")),\nperson(given = \"Nick\",\nfamily = \"Golding\",\nrole = \"aut\",\nemail = \"nick.golding.research@gmail.com\",\ncomment = c(ORCID = \"0000-0001-8916-5570\")),\nperson(given = \"Aarathy\",\nfamily = \"Babu\",\nrole = c(\"aut\"),\nemail = \"aarathybabu907@gmail.com\",\ncomment = c(ORCID = \"0000-0002-6982-5989\")),\nperson(given = \"Chitra\",\nfamily = \"Saraswati\",\nrole = c(\"aut\"),\nemail = \"chitra.saraswati@telethonkids.org.au\",\ncomment = c(ORCID = \"0000-0002-8159-0414\")),\nperson(given = \"Michael\",\nfamily = \"Lydeamore\",\nrole = \"aut\",\nemail = \"michael.lydeamore@monash.edu\",\ncomment = c(ORCID = 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"page": "autoplot-conmat", "title": "Plot setting matrices using ggplot2", "topics": [ "autoplot-conmat", "autoplot.conmat_age_matrix", "autoplot.conmat_setting_prediction_matrix", "autoplot.ngm_setting_matrix", "autoplot.setting_vaccination_matrix", "autoplot.transmission_probability_matrix" ] }, { "page": "autoplot-conmat-partial", "title": "Plot partial predictive plots using ggplot2", "topics": [ "autoplot-conmat-partial", "autoplot.partial_predictions", "autoplot.partial_predictions_sum", "autoplot.setting_partial_predictions", "autoplot.setting_partial_predictions_sum" ] }, { "page": "conmat_original_school_demographics", "title": "Original school demographics for conmat", "topics": [ "conmat_original_school_demographics" ] }, { "page": "conmat_original_work_demographics", "title": "Original work demographics for conmat", "topics": [ "conmat_original_work_demographics" ] }, { "page": "conmat_population", "title": "Define a conmat population", "topics": [ "conmat_population" ] }, { "page": "data_abs_lga_education", "title": "LGA wise ABS education population data on different ages for year 2016", "topics": [ "data_abs_lga_education" ] }, { "page": "data_abs_lga_work", "title": "LGA wise ABS work population data on different ages for year 2016", "topics": [ "data_abs_lga_work" ] }, { "page": "data_abs_state_education", "title": "State wise ABS education population data on different ages for year 2016", "topics": [ "data_abs_state_education" ] }, { "page": "data_abs_state_work", "title": "State wise ABS work population data on different ages for year 2016", "topics": [ "data_abs_state_work" ] }, { "page": "davies_age_extended", "title": "Susceptibility and clinical fraction parameters from Davies et al.", "topics": [ "davies_age_extended" ] }, { "page": "estimate_setting_contacts", "title": "Get predicted setting specific as well as combined contact matrices", "topics": [ "estimate_setting_contacts" ] }, { "page": "extrapolate_polymod", "title": "Fit all-of-polymod model and extrapolate to a given population an age breaks", "topics": [ "extrapolate_polymod" ] }, { "page": "eyre_transmission_probabilities", "title": "Transmission probabilities of COVID19 from Eyre et al.", "topics": [ "eyre_transmission_probabilities" ] }, { "page": "fit_setting_contacts", "title": "Fit a contact model to a survey population", "topics": [ "fit_setting_contacts" ] }, { "page": "fit_single_contact_model", "title": "Fit a single GAM contact model to a dataset", "topics": [ "fit_single_contact_model" ] }, { "page": "generate_ngm", "title": "Calculate next generation contact matrices", "topics": [ "generate_ngm", "generate_ngm.conmat_population", "generate_ngm.conmat_setting_prediction_matrix" ] }, { "page": "generate_ngm_oz", "title": "Calculate next generation contact matrices from ABS data", "topics": [ "generate_ngm_oz" ] }, { "page": "get_abs_household_size_distribution", "title": "Get household size distribution based on state or LGA name", "topics": [ "get_abs_household_size_distribution" ] }, { "page": "get_abs_household_size_population", "title": "Get population associated with each household size in an LGA or a state", "topics": [ "get_abs_household_size_population" ] }, { "page": "get_abs_per_capita_household_size", "title": "Get per capita household size based on state or LGA name", "topics": [ "get_abs_per_capita_household_size" ] }, { "page": "get_abs_per_capita_household_size_lga", "title": "Get household size distribution based on LGA name", "topics": [ "get_abs_per_capita_household_size_lga" ] }, { "page": "get_abs_per_capita_household_size_state", "title": "Get household size distribution based on state name", "topics": [ "get_abs_per_capita_household_size_state" ] }, { "page": "get_age_population_function", "title": "Return an interpolating function for populations in 1y age increments", "topics": [ "get_age_population_function", "get_age_population_function.conmat_population", "get_age_population_function.data.frame" ] }, { "page": "get_polymod_contact_data", "title": "Format POLYMOD data and filter contacts to certain settings", "topics": [ "get_polymod_contact_data" ] }, { "page": "get_polymod_per_capita_household_size", "title": "Get polymod per capita household size.", "topics": [ "get_polymod_per_capita_household_size" ] }, { "page": "get_polymod_population", "title": "Return the polymod-average population age distribution in 5y", "topics": [ "get_polymod_population" ] }, { "page": "get_polymod_setting_data", "title": "Get polymod setting data", "topics": [ "get_polymod_setting_data" ] }, { "page": "get_setting_transmission_matrices", "title": "Get Setting Transmission Matrices", "topics": [ "get_setting_transmission_matrices" ] }, { "page": "matrix_to_predictions", "title": "Convert a contact matrix as output into a long-form tibble", "topics": [ "matrix_to_predictions" ] }, { "page": "new_age_matrix", "title": "Build new age matrix", "topics": [ "new_age_matrix" ] }, { "page": "new_ngm_setting_matrix", "title": "Establish new BGM setting data", "topics": [ "new_ngm_setting_matrix" ] }, { "page": "new_setting_data", "title": "Establish new setting data", "topics": [ "new_setting_data" ] }, { "page": "partial-prediction", "title": "Create partial predictions and partial prediction plots.", "topics": [ "partial-prediction", "partial_effects", "partial_effects.contact_model", "partial_effects.setting_contact_model", "partial_effects_sum.setting_contact_model" ] }, { "page": "partial-prediction-sum", "title": "Create partial predictive plots for a set of fitted models.", "topics": [ "partial-prediction-sum", "partial_effects_sum", "partial_effects_sum.contact_model" ] }, { "page": "per_capita_household_size", "title": "Get per capita household size with household size distribution", "topics": [ "per_capita_household_size" ] }, { "page": "polymod", "title": "Social contact data from 8 European countries (imported from 'socialmixr')", "topics": [ "polymod" ] }, { "page": "polymod_setting_models", "title": "Polymod Settings models", "topics": [ "polymod_setting_models" ] }, { "page": "predict_contacts", "title": "Predict contact rate between two age populations, given some model.", "topics": [ "predict_contacts" ] }, { "page": "predict_contacts_1y", "title": "Predict contact rate to a given population at full 1y resolution", "topics": [ "predict_contacts_1y" ] }, { "page": "predict_setting_contacts", "title": "Predict setting contacts", "topics": [ "predict_setting_contacts" ] }, { "page": "predictions_to_matrix", "title": "Convert dataframe of predicted contacts into matrix", "topics": [ "predictions_to_matrix" ] }, { "page": "prem_germany_contact_matrices", "title": "Contact matrices as calculated by Prem. et al.", "topics": [ "prem_germany_contact_matrices" ] }, { "page": "raw_eigenvalue", "title": "Get raw eigvenvalue from NGM matrix", "topics": [ "raw_eigenvalue" ] }, { "page": "scaling", 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