devtools::build_readme()

README.Rmd

@@ -13,17 +13,19 @@ knitr::opts_chunk$set(
     fig.path = "man/figures/README-", 
     dpi = 100
 )
-devtools::load_all()
 ```
 
 
 # timetk for R
 
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+
 
 >  Making time series analysis in R easier.
 
@@ -52,7 +54,7 @@ There are _many_ R packages for working with Time Series data. Here's how `timet
 
 <div class = "comparison">
 
-| Task                         | [timetk](https://business-science.github.io/timetk/) | [tsibble](https://tsibble.tidyverts.org/index.html) | [feasts](https://feasts.tidyverts.org/index.html) | [tibbletime](https://business-science.github.io/tibbletime/) |
+| Task                         | [timetk](https://business-science.github.io/timetk/) | [tsibble](https://tsibble.tidyverts.org/index.html) | [feasts](https://feasts.tidyverts.org/index.html) | [tibbletime (retired)](https://business-science.github.io/tibbletime/) |
 |------------------------------|--------|---------|---------|-------------|
 | __Structure__            |        |         |         |             |             
 | Data Structure               | tibble (tbl)  | tsibble (tbl_ts)| tsibble (tbl_ts) | tibbletime (tbl_time)  |
@@ -160,7 +162,7 @@ The `timetk` package wouldn't be possible without other amazing time series pack
 * [lubridate](https://lubridate.tidyverse.org/): `timetk` makes heavy use of `floor_date()`, `ceiling_date()`, and `duration()` for "time-based phrases". 
     - Add and Subtract Time (`%+time%` & `%-time%`): `"2012-01-01" %+time% "1 month 4 days"` uses `lubridate` to intelligently offset the day
 * [xts](https://github.com/joshuaulrich/xts): Used to calculate periodicity and fast lag automation. 
-* [forecast (retired)](https://pkg.robjhyndman.com/forecast/): Possibly my favorite R package of all time. It's based on `ts`, and it's predecessor is the `tidyverts` (`fable`, `tsibble`, `feasts`, and `fabletools`). 
+* [forecast (retired)](https://pkg.robjhyndman.com/forecast/): Possibly my favorite R package of all time. It's based on `ts`, and its predecessor is the `tidyverts` (`fable`, `tsibble`, `feasts`, and `fabletools`). 
     - The `ts_impute_vec()` function for low-level vectorized imputation using STL + Linear Interpolation uses `na.interp()` under the hood. 
     - The `ts_clean_vec()` function for low-level vectorized imputation using STL + Linear Interpolation uses `tsclean()` under the hood.
     - Box Cox transformation `auto_lambda()` uses `BoxCox.Lambda()`.