docs: add roadmap

Author: atsyplenkov

.github/CONTRIBUTING.md

@@ -45,3 +45,20 @@ The package uses a lot of C++ code via the Rcpp package. Therefore, it is expect
 ## Code of Conduct
 
 Please note that the tidyhydro project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By contributing to this project you agree to abide by its terms.
+
+## Roadmap
+### GOF
+-[ ] KGE''
+
+-[ ] KGE Score
+
+### Regression
+-[ ] PPCC - maximizes the probability plot correlation coefficient [@helselStatisticalMethodsWater2002, p.253]
+
+-[ ] SSE - minimize sum of square errors [@helselStatisticalMethodsWater2002, p.253]
+
+-[ ] BCF - Duan's bias correction factor for log, log10 and log2 [@rasmussenGuidelinesProceduresComputing2009, p. 17]
+
+-[ ] MSPE - model standard percentage error log and nonlog [@rasmussenGuidelinesProceduresComputing2009, p. 13]
+
+-[ ] RMSE

README.Rmd

@@ -42,7 +42,6 @@ The `tidyhydro` package follows the philosophy of [`yardstick`](https://github.c
 
 ```{r example}
 library(tidyhydro)
-data(avacha)
 str(avacha)
 
 kge(avacha, obs, sim)

README.md

@@ -45,7 +45,6 @@ can estimate `KGE`, `NSE` or `pBIAS` for a data frame like this:
 
 ``` r
 library(tidyhydro)
-data(avacha)
 str(avacha)
 #> Classes 'tbl_df', 'tbl' and 'data.frame':    365 obs. of  3 variables:
 #>  $ date: Date, format: "2022-01-01" "2022-01-02" ...
@@ -129,9 +128,9 @@ bench::mark(
 #> # A tibble: 3 × 6
 #>   expression   min median `itr/sec` mem_alloc `gc/sec`
 #>   <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>
-#> 1 tidyhydro   1       1       29.2        NaN      NaN
-#> 2 hydroGOF   15.1    19.1      1          Inf      Inf
-#> 3 baseR       8.47   10.4      2.42       Inf      Inf
+#> 1 tidyhydro   1       1       22.7        NaN      NaN
+#> 2 hydroGOF   15.2    19.1      1          Inf      Inf
+#> 3 baseR       8.66   10.6      2.44       Inf      Inf
 ```
 
 ## Code of Conduct