README.md

In ericward-noaa/pinkescape: Simulate Pink Salmon Escapement

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pinkescape

Repo for simulating pink salmon escapement

Installation

```{r, eval=FALSE}

install.packages("remotes")

remotes::install_github("ericward-noaa/pinkescape", dependencies = TRUE)

## Usage

The package consists of a single function for simulating data, with the following arguments. Additional details can be found in the help file 

```{r, eval=TRUE}
library(pinkescape)

df = sim(
  sims = 1000,
  time_steps = 100,
  pr_12 = 0.1,
  pr_21 = 0.1,
  run = "odd",
  deterministic_model = TRUE,
  rec_std = 0.1,
  rec_acf = 0.7,
  escapement_rule = "both",
  discount_rate = 0.1,
  seed = 123
)

Plotting output

```{r, eval=TRUE} library(ggplot2) p1 <- ggplot(df, aes(t, regime)) + geom_point() + geom_line() + theme_bw() + xlab("Time") + ylab("Regime") p2 <- ggplot(df, aes(t, spawners)) + geom_point() + geom_line() + theme_bw() + xlab("Time") + ylab("Spawners") p3 <- ggplot(df, aes(t, rec)) + geom_point() + geom_line() + theme_bw() + xlab("Time") + ylab("Recruitment") p4 <- ggplot(df, aes(t, harvest)) + geom_point() + geom_line() + theme_bw() + xlab("Time") + ylab("Harvest") p5 <- ggplot(df, aes(t, harvest)) + geom_point() + geom_line() + theme_bw() + xlab("Time") + ylab("Benefits") gridExtra::grid.arrange(p1,p2,p3,p4,p5,ncol=2)

## Calculating net benefits across simulations

```{r, eval=TRUE}
# calculate product
df$discount_nb = df$net_benefits*df$discount

# calculate the sum for each simulation
library(dplyr)
summary = dplyr::group_by(df, sim) %>% 
dplyr::summarise(tot_ben = sum(discount_nb))

ggplot(summary, aes(tot_ben)) + geom_histogram() + 
xlab("Total benefits")

ericward-noaa/pinkescape documentation built on Sept. 21, 2023, 7:19 a.m.