From fca5563e4284d6a842b6686117da35fead972486 Mon Sep 17 00:00:00 2001
From: Margarete Walden <maw32@humboldt.edu>
Date: Fri, 10 May 2024 23:56:25 -0700
Subject: [PATCH] Replace sim_variables.R
---
scripts/sim_variables.R | 148 ++++++++++++++++++++--------------------
1 file changed, 74 insertions(+), 74 deletions(-)
diff --git a/scripts/sim_variables.R b/scripts/sim_variables.R
index 3566058..7cdfc0d 100644
--- a/scripts/sim_variables.R
+++ b/scripts/sim_variables.R
@@ -1,75 +1,75 @@
-####
-####----1. ABOUT------------------------------------------------------------####
-####
-#### Evaluating alternative methods for modeling trap
-#### efficiencies of outmigrating juvenile salmonids
-####
-#### Authors: Walden et al.
-####
-#### Content: R-Code for sourcing declared variables.
-####
-#### This is the file for Supplement X of the manuscript.
-####
-
-####----2. "True" parameter values for simulated data-----------------------####
-
-## Covariates
-Qmin <- 500 # discharge
-Qmax <- 7000 # discharge
-degCmin <- 6 # temperature
-degCmax <- 21 # temperature
-effortmin <- 720 # effort
-effortmax <- 3840 # effort
-precipitation <- 0 # precipitation (yes/no) (nuisance)
-nyear <- 10 # groups (random effects)
-
-## Set parameter values
-Beta0_maxpt1 <- -3.2 # Trap efficiency max 0.10
-Beta0_maxpt25 <- -2.1 # Trap efficiency max 0.25
-Beta1 <- -0.3 # discharge
-Beta2 <- 0.2 # temperature
-Beta3 <- 0.2 # effort
-Beta4 <- 0.0 # precipitation yes/no
-Beta5 <- -0.4 # effort^2
-Beta6 <- 0.4 # discharge x temperature interaction
-raneffSD <- 0.1 # year effect standard deviation
-phiTrue <- 0.0002
-
-####----3. Simulation variables---------------------------------------------####
-
-# vector of sample sizes to test
-nset <- c(50,100,150,200)
-# vector of trap efficiencies to test
-theseefficiencies <- c("Max efficiency 0.1","Max efficiency 0.25")
-# Number of simulations to complete
-nsim <- 1000
-# number of MCMC samples to extract for marginal predictions
-nsample <- 1000
-# size of test dataset
-ntest <- 100
-
-####----4. Model parameters, hyperparameters, or variables------------------####
-
-## For boosted regression modeling
-seed.cvrisk <- 143180916
-mutuneiter <- 2000
-phituneiter <- 2000
-nu_hp=0.1
-fmu <- as.formula(y ~ 1 +
- bols(discharge, intercept=FALSE) +
- bols(temperature, intercept=FALSE) +
- bols(effort, intercept=FALSE) +
- bols(precip, intercept=FALSE) +
- bbs(effort, knots=2, boundary.knots=NULL, degree=2,
- df=1, center=TRUE) +
- bols(temperature, intercept=FALSE, df=1) %X%
- bols(discharge, intercept=FALSE, df=1) +
- brandom(year)
-)
-fphi <- as.formula(y ~ 1)
-nboot <- 1000
-kfoldB <- 25
-
-## For random forest modeling
-seed.forest <- 234672817
+####
+####----1. ABOUT------------------------------------------------------------####
+####
+#### Evaluating alternative methods for modeling trap
+#### efficiencies of outmigrating juvenile salmonids
+####
+#### Authors: Walden et al.
+####
+#### Content: R-Code for sourcing declared variables.
+####
+#### This is the file for Supplement X of the manuscript.
+####
+
+####----2. "True" parameter values for simulated data-----------------------####
+
+## Covariates
+Qmin <- 500 # discharge
+Qmax <- 7000 # discharge
+degCmin <- 6 # temperature
+degCmax <- 21 # temperature
+effortmin <- 720 # effort
+effortmax <- 3840 # effort
+precipitation <- 0 # precipitation (yes/no) (nuisance)
+nyear <- 10 # groups (random effects)
+
+## Set parameter values
+Beta0_maxpt1 <- -3.2 # Trap efficiency max 0.10
+Beta0_maxpt25 <- -2.1 # Trap efficiency max 0.25
+Beta1 <- -0.3 # discharge
+Beta2 <- 0.2 # temperature
+Beta3 <- 0.2 # effort
+Beta4 <- 0.0 # precipitation yes/no
+Beta5 <- -0.4 # effort^2
+Beta6 <- 0.4 # discharge x temperature interaction
+raneffSD <- 0.1 # year effect standard deviation
+phiTrue <- 0.0002
+
+####----3. Simulation variables---------------------------------------------####
+
+# vector of sample sizes to test
+nset <- c(50,100,150,200)
+# vector of trap efficiencies to test
+theseefficiencies <- c("Max efficiency 0.1","Max efficiency 0.25")
+# Number of simulations to complete
+nsim <- 1000
+# number of MCMC samples to extract for marginal predictions
+nsample <- 1000
+# size of test dataset
+ntest <- 100
+
+####----4. Model parameters, hyperparameters, or variables------------------####
+
+## For boosted regression modeling
+seed.cvrisk <- 143180916
+mutuneiter <- 2000
+phituneiter <- 2000
+nu_hp=0.1
+fmu <- as.formula(y ~ 1 +
+ bols(discharge, intercept=FALSE) +
+ bols(temperature, intercept=FALSE) +
+ bols(effort, intercept=FALSE) +
+ bols(precip, intercept=FALSE) +
+ bbs(effort, knots=2, boundary.knots=NULL, degree=2,
+ df=1, center=TRUE) +
+ bols(temperature, intercept=FALSE, df=1) %X%
+ bols(discharge, intercept=FALSE, df=1) +
+ brandom(year)
+)
+fphi <- as.formula(y ~ 1)
+nboot <- 1000
+kfoldB <- 25
+
+## For random forest modeling
+seed.forest <- 234672817
rftrees <- 2000
\ No newline at end of file
--
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