R package: mriptools

This is a draft library for MRIP data exploration, including outlier analysis. The data and variables used are here: https://www.st.nmfs.noaa.gov/st1/recreational/MRIP_Estimate_Data/

Requirements

The following software/R libraries are required to install the package...

• R (version >= 4.4.3)
• devtools
• ggplot2

How to install

Run the following line in R: devtools::install_github("dendroica/mriptools")

How to update the package

Run the following line in R: devtools::update_packages("mriptools")

Instructions

Below is an example R script to run the AnalyzeMRIPOutliers() function to identify outliers in the preliminary year. Outlier analysis is performed with respect to a baseline timespan you set in comparison_timespan. Set the FIPS code for your state:
GA=13, SC=45, NC=37, VA=51, MD=24, DE=10, NJ=34, NY=36, CT=9, RI=44, MA=25, NH=33, ME=23
Set the out_dir variable to the folder where output plots and CSV files will be generated. The in_dir argument is optional, and points to a location with your downloaded files. If this option is not set, the default behavior is to pull the data directly from the data repository online: https://www.st.nmfs.noaa.gov/st1/recreational/MRIP_Estimate_Data/CSV/Wave%20Level%20Estimate%20Downloads

If you choose to use input files stored locally on your computer, be sure that there are not duplicate files for a given year in the in_dir folder (e.g. a preliminary and final file for a given year). The remaining variables are used in the graphing outputs later. You can change the species of interest for your state, the waves included, the areas, and the modes that you would like included on your graphs. You might want to watch how many species are included as it may take a little bit for the graphing function to loop through a ton of species.

library(mriptools)

myspecies <- c(
  "ATLANTIC CROAKER",
  "BLACK DRUM",
  "BLACK SEA BASS",
  "BLUEFISH",
  "COBIA",
  "DOLPHIN",
  "RED DRUM",
  "STRIPED BASS",
  "SUMMER FLOUNDER",
  "TAUTOG"
)

my_outdir <- "~/output/mrip_ex"

AnalyzeMRIPOutliers(
  comparison_timespan = 2017:2024,
  prelim_yr = 2025,
  species = myspecies,
  waves = c(2, 3, 4, 5, 6),
  areas = c("INLAND", "OCEAN (<= 3 MI)", "OCEAN (> 3 MI)"),
  modes = c("CHARTER BOAT", "PARTY BOAT", "PRIVATE/RENTAL BOAT", "SHORE"),
  state = 24,
  out_dir = my_outdir
) # in_dir="~/data/MRIP",

Output

• val: the value for the prelim year
• n: the number of years in comparison_timespan that the species was observed in the given wave, and thus reflects how many values went into calculating the summary stats