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Copy path03_Dredge_hake_Pre_to_Age0.R
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03_Dredge_hake_Pre_to_Age0.R
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rm(list=ls()) # Clear variables in workspace
library(MuMIn) # load package with dredge
##### prepare fish data ####
# main = getwd()
MainFile = "/Users/cathleen.vestfals/Desktop/NRC_Hake_Kristin_Marshall/Data/Hake_Analysis"
DredgeFile = paste0(MainFile,"/03_Dredge")
dir.create(DredgeFile)
setwd(DredgeFile)
####################################################################
##### BRING IN HAKE DATA - preconditioning to age-0 ################
####################################################################
fish00 = data.frame(read.table(paste0(MainFile,'/00_Data/hake.data_2020_medians.csv'), header=TRUE, sep=","))
head(fish00)
max(fish00$year)
years = 1980:2010 # only have ROMS data 1980-2010
fish = fish00[fish00$year %in% years,]
roms = data.frame(read.csv(paste0(MainFile,'/01_ROMS_Prelim/Data_ROMS.for.hake.analysis.pre_to_age0.csv'), header=TRUE))
roms = roms[roms$year %in% years,]
##########################################
#### RUN MODEL FITTING ###################
##########################################
# roms = the roms data after processing
#### Build equation ####
for(j in 2:ncol(roms)){# build equation
x1 = colnames(roms)[j]
if(j==ncol(roms)){x2 = x1}else{x2 = paste(x1,"+")}
if(j==2){ROMS = x2}else{ROMS = paste(ROMS,x2)}
}
ROMS
#### Set up Formula #### variables with AIC < 2 (AIC - AICq)
form_dredge = as.formula(paste('dev ~ I(CSTlarv.s^2) + I(CSTlatelarv.s^2) + ', ROMS, sep=''))
#
form_dredge
saveRDS(form_dredge, "Formula_for_Dredge.hake_pre_to_age0.rds")
#### Prep & combine data ####
# data_1 = # combine roms data and resids
data_1 = merge(fish,roms, 'year')
data_1 = na.omit(data_1)
write.table(data_1, 'Analyzed.data.hake.stage_pre_to_age0.csv',sep=',',col.names = TRUE, row.names = FALSE)
###############################################################################
##### run dredge twice ########################################################
##### once full, once minus the last five years ###############################
##### save output ###############################
###############################################################################
fit = lm(form_dredge, data=data_1, na.action = na.fail)
#### Run Dredge and save results ####
mtable = dredge(fit, rank = AICc, m.lim = c(NA,5),
subset= # block correlated terms from the model > 0.70
!(ASTyolk && ASTlarv) && # 0.83
!(CSTlarv.s && CSTlatelarv.s) && # 0.94
dc(CSTlarv.s, I(CSTlarv.s^2)) &&
dc(CSTlatelarv.s, I(CSTlatelarv.s^2)),
extra = list(R2 = function(x)
summary(x)$r.squared[[1]],
F = function(y)
summary(y)$fstatistic[[1]]),
trace=2 )
mtable2 = subset(mtable, delta < 2)
mtable2
print(mtable2, abbrev.names = FALSE)
saveRDS(mtable, file='Table_model.fits.hake_pre_to_age0.rds')
write.csv(mtable2,"R_Table_Delta2.hake_pre_to_age0.csv")
mtable = readRDS('Table_model.fits.hake_pre_to_age0.rds')
mtable2 = subset(mtable, delta < 2)
mtable2
setwd(MainFile)