Package index

`epi_df` basics

Details on epi_df format, and basic functionality.

as_tibble(<epi_df>): Convert to tibble

as_tsibble(<epi_df>): Convert to tsibble format

autoplot(<epi_df>): Automatically plot an epi_df

complete(<epi_df>): Complete epi_df

as_epi_df() new_epi_df(): epi_df object

group_epi_df(): Group an epi_df object by default keys

is_epi_df(): Test for epi_df format

print(<epi_df>) group_by(<epi_df>) ungroup(<epi_df>) group_modify(<epi_df>) unnest(<epi_df>): Base S3 methods for an epi_df object

sum_groups_epi_df(): Aggregate an epi_df object

summary(<epi_df>): Summarize epi_df object

geo_column_names(): potential geo_value columns

time_column_names(): potential time_value columns

version_column_names(): potential version columns

`epi_*()` functions

Functions that act on epi_df objects.

epi_slide(): Slide a function over variables in an epi_df object

epi_slide_mean(): Optimized slide function for performing rolling averages on an epi_df object

epi_slide_sum(): Optimized slide function for performing rolling sums on an epi_df object

epi_slide_opt(): Optimized slide function for performing common rolling computations on an epi_df object

epi_cor(): Compute correlations between variables in an epi_df object

Vector functions

Functions that act directly on signal variables.

growth_rate(): Estimate growth rate

detect_outlr(): Detect outliers

detect_outlr_rm(): Detect outliers based on a rolling median

detect_outlr_stl(): Detect outliers based on an STL decomposition

`epi_archive` basics

Details on epi_archive, and basic functionality.

archive_cases_dv_subset: Subset of daily doctor visits and cases in archive format

clone(): Clone an epi_archive object.

new_epi_archive() validate_epi_archive() as_epi_archive(): epi_archive object

epix_slide(): Slide a function over variables in an epi_archive or grouped_epi_archive

epix_truncate_versions_after(): Filter an epi_archive object to keep only older versions

group_by(<epi_archive>) group_by(<grouped_epi_archive>) group_by_drop_default(<grouped_epi_archive>) group_vars(<grouped_epi_archive>) groups(<grouped_epi_archive>) ungroup(<grouped_epi_archive>) is_grouped_epi_archive(): group_by and related methods for epi_archive, grouped_epi_archive

print(<epi_archive>): Print information about an epi_archive object

revision_summary(): A function to describe revision behavior for an archive

`epix_*()` functions

Functions that act on an epi_archive and/or grouped_epi_archive object.

epix_as_of(): Generate a snapshot from an epi_archive object

epix_fill_through_version(): Fill epi_archive unobserved history

epix_merge(): Merge two epi_archive objects

epix_slide(): Slide a function over variables in an epi_archive or grouped_epi_archive

epix_truncate_versions_after(): Filter an epi_archive object to keep only older versions

group_by(<epi_archive>) group_by(<grouped_epi_archive>) group_by_drop_default(<grouped_epi_archive>) group_vars(<grouped_epi_archive>) groups(<grouped_epi_archive>) ungroup(<grouped_epi_archive>) is_grouped_epi_archive(): group_by and related methods for epi_archive, grouped_epi_archive

Example data

archive_cases_dv_subset: Subset of daily doctor visits and cases in archive format

incidence_num_outlier_example: Subset of JHU daily cases from California and Florida

jhu_csse_county_level_subset: Subset of JHU daily cases from counties in Massachusetts and Vermont

jhu_csse_daily_subset: Subset of JHU daily state cases and deaths

Basic automatic plotting

autoplot(<epi_df>): Automatically plot an epi_df

Advanced internals

compactify: Compactify

epiprocess-package epiprocess: epiprocess: Tools for basic signal processing in epidemiology

max_version_with_row_in(): max(x$version), with error if x has 0 rows

next_after(): Get the next possible value greater than x of the same type

guess_period() experimental: Use max valid period as guess for period of time_values

key_colnames(): Grab any keys associated to an epi_df

epi_df basics

epi_*() functions