Merge pull request #411 from cmu-delphi/ds/doc

doc: update installation instructions to reference stable branch

Author: dshemetov

README.md

@@ -1,14 +1,28 @@
 # epiprocess
- 
- <!-- badges: start -->
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-  <!-- badges: end -->
+
+<!-- badges: start -->
+
+[![R-CMD-check](https://github.com/cmu-delphi/epiprocess/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/cmu-delphi/epiprocess/actions/workflows/R-CMD-check.yaml)
+
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 This package introduces a common data structure for epidemiological data sets
 measured over space and time, and offers associated utilities to perform basic
 signal processing tasks. See the getting started guide and vignettes for
 examples.
 
+## Installation
+
+To install (unless you're making changes to the package, use the stable version):
+
+```r
+# Stable version
+pak::pkg_install("cmu-delphi/epiprocess@main")
+
+# Dev version
+pak::pkg_install("cmu-delphi/epiprocess@dev")
+```
+
 ## `epi_df`: snapshot of a data set
 
 The first main data structure in the `epiprocess` package is called
@@ -20,28 +34,26 @@ contains the most up-to-date values of the signals variables, as of a given
 time.
 
 By convention, functions in the `epiprocess` package that operate on `epi_df`
-objects begin with `epi`. For example: 
+objects begin with `epi`. For example:
 
-- `epi_slide()`, for iteratively applying a custom computation to a variable in
-  an `epi_df` object over sliding windows in time;
-  
-- `epi_cor()`, for computing lagged correlations between variables in an
-  `epi_df` object, (allowing for grouping by geo value, time value, or any other
-  variables).
+-   `epi_slide()`, for iteratively applying a custom computation to a variable in
+    an `epi_df` object over sliding windows in time;
+-   `epi_cor()`, for computing lagged correlations between variables in an
+    `epi_df` object, (allowing for grouping by geo value, time value, or any other
+    variables).
 
 Functions in the package that operate directly on given variables do not begin
-  with `epi`. For example: 
-
-- `growth_rate()`, for estimating the growth rate of a given signal at given
-  time values, using various methodologies;
+with `epi`. For example:
 
-- `detect_outlr()`, for detecting outliers in a given signal over time, using
-  either built-in or custom methodologies.
+-   `growth_rate()`, for estimating the growth rate of a given signal at given
+    time values, using various methodologies;
+-   `detect_outlr()`, for detecting outliers in a given signal over time, using
+    either built-in or custom methodologies.
 
 ## `epi_archive`: full version history of a data set
 
 The second main data structure in the package is called
-[`epi_archive`](reference/epi_archive.html). This is a special class (R6 format) 
+[`epi_archive`](reference/epi_archive.html). This is a special class (R6 format)
 wrapped around a data table that stores the archive (version history) of some
 signal variables of interest.
 
@@ -50,20 +62,17 @@ By convention, functions in the `epiprocess` package that operate on
 "archive"). These are just wrapper functions around the public methods for the
 `epi_archive` R6 class. For example:
 
-- `epix_as_of()`, for generating a snapshot in `epi_df` format from the data
-  archive, which represents the most up-to-date values of the signal variables,
-  as of the specified version;
-  
-- `epix_fill_through_version()`, for filling in some fake version data following
-  simple rules, for use when downstream methods expect an archive that is more
-  up-to-date (e.g., if it is a forecasting deadline date and one of our data
-  sources cannot be accessed to provide the latest versions of its data)
-
-- `epix_merge()`, for merging two data archives with each other, with support
-  for various approaches to handling when one of the archives is more up-to-date
-  version-wise than the other;
-
-- `epix_slide()`, for sliding a custom computation to a data archive over local
-  windows in time, much like `epi_slide` for an `epi_df` object, but with one
-  key difference: the sliding computation at any given reference time t is
-  performed only on the **data that would have been available as of t**.
+-   `epix_as_of()`, for generating a snapshot in `epi_df` format from the data
+    archive, which represents the most up-to-date values of the signal variables,
+    as of the specified version;
+-   `epix_fill_through_version()`, for filling in some fake version data following
+    simple rules, for use when downstream methods expect an archive that is more
+    up-to-date (e.g., if it is a forecasting deadline date and one of our data
+    sources cannot be accessed to provide the latest versions of its data)
+-   `epix_merge()`, for merging two data archives with each other, with support
+    for various approaches to handling when one of the archives is more up-to-date
+    version-wise than the other;
+-   `epix_slide()`, for sliding a custom computation to a data archive over local
+    windows in time, much like `epi_slide` for an `epi_df` object, but with one
+    key difference: the sliding computation at any given reference time t is
+    performed only on the **data that would have been available as of t**.