/
generate-model-fit.R
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generate-model-fit.R
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#####################################
# Brandon Edwards
# melodus-analysis
# generate-model-fit.R
# Created December 2017
# Last Updated December 2017
#####################################
#####################################
# Clear Memory
#####################################
remove(list = ls())
#####################################
# Import Libraries and Files
#####################################
#install.packages("easynls")
library(easynls)
library(ggplot2)
#####################################
# Read Data
#####################################
baseData <- read.csv("baseDataSet.csv")
treatmentData <- read.csv("treatmentDataSet.csv")
#####################################
# Set Constants
#####################################
# From Martens and Goossen 2008
K.exp <- 0.084
I.exp <- 11.271
A.exp <- 53.4
#####################################
# Base Estimate Generation
#####################################
A.Base <- NULL
I.Base <- NULL
K.Base <- NULL
K.Base.AbsBias <- NULL
I.Base.AbsBias <- NULL
A.Base.AbsBias <- NULL
for (i in unique(baseData$Run))
{
data <- baseData[ which(baseData$Run == i), ]
fit <- nlsfit(data[c("Day", "Mean.Weight")], model=10, start=c(200,4,0.05))
A.Base <- c(A.Base, fit$Parameters[1,1])
I.Base <- c(I.Base, fit$Parameters[2,1])
K.Base <- c(K.Base, fit$Parameters[3,1])
A.Base.AbsBias <- c(A.Base.AbsBias, (fit$Parameters[1,1] - A.exp))
I.Base.AbsBias <- c(I.Base.AbsBias, (fit$Parameters[2,1] - I.exp))
K.Base.AbsBias <- c(K.Base.AbsBias, (fit$Parameters[3,1] - K.exp))
}
A.Base.RelBias <- (A.Base.AbsBias/A.exp)*100
I.Base.RelBias <- (I.Base.AbsBias/I.exp)*100
K.Base.RelBias <- (K.Base.AbsBias/K.exp)*100
baseEstimates <- cbind(A.Base, I.Base, K.Base)
baseEstimates <- data.frame(baseEstimates)
names(baseEstimates) <- c("A.Est", "I.Est", "K.Est")
write.csv(baseEstimates, "output/fitAnalysis/baseEstimates.csv", row.names = FALSE)
baseEstimatesBias <- cbind(A.Base.AbsBias, I.Base.AbsBias, K.Base.AbsBias,
A.Base.RelBias, I.Base.RelBias, K.Base.RelBias)
baseEstimatesBias <- data.frame(baseEstimatesBias)
names(baseEstimatesBias) <- c("A.AbsBias", "I.AbsBias", "K.AbsBias",
"A.RelBias", "I.RelBias", "K.RelBias")
write.csv(baseEstimatesBias, "output/fitAnalysis/baseEstimatesBias.csv", row.names = FALSE)
#####################################
# Non-Exclosure Estimate Generation
#####################################
dataNoExclosure <- treatmentData[ which(treatmentData$Excl.Rad == "No Exclosure"), ]
noExclosureEstimates <- NULL
for (anthro in unique(dataNoExclosure$Anthro))
{
eval(parse(text = paste("A.", anthro, ".N <- NULL", sep = "")))
eval(parse(text = paste("I.", anthro, ".N <- NULL", sep = "")))
eval(parse(text = paste("K.", anthro, ".N <- NULL", sep = "")))
# eval(parse(text = paste("A.", anthro, ".AbsBias <- NULL", sep = "")))
# eval(parse(text = paste("I.", anthro, ".AbsBias <- NULL", sep = "")))
# eval(parse(text = paste("K.", anthro, ".AbsBias <- NULL", sep = "")))
data <- dataNoExclosure[ which(dataNoExclosure$Anthro == anthro), ]
for (i in unique(data$Run))
{
dataTemp <- data[ which(data$Run == i), ]
fit <- nlsfit(dataTemp[c("Day", "Mean.Weight")], model=10, start=c(200,4,0.05))
#Push parameter estimates
eval(parse(text = paste("A.",
anthro,
".N <- c(
eval(parse(text = paste(\"A.\", anthro, \".N\", sep = \"\"))),
(fit$Parameters[1,1]))",
sep = "")))
eval(parse(text = paste("I.",
anthro,
".N <- c(
eval(parse(text = paste(\"I.\", anthro, \".N\", sep = \"\"))),
(fit$Parameters[2,1]))",
sep = "")))
eval(parse(text = paste("K.",
anthro,
".N <- c(
eval(parse(text = paste(\"K.\", anthro, \".N\", sep = \"\"))),
(fit$Parameters[3,1]))",
sep = "")))
#Push absolute bias, do we need this?
# eval(parse(text = paste("A.",
# anthro,
# ".AbsBias <- c(
# eval(parse(text = paste(\"A.\", anthro, \".AbsBias\", sep = \"\"))),
# (fit$Parameters[1,1] - A.exp))",
# sep = "")))
# eval(parse(text = paste("I.",
# anthro,
# ".AbsBias <- c(
# eval(parse(text = paste(\"I.\", anthro, \".AbsBias\", sep = \"\"))),
# (fit$Parameters[2,1] - I.exp))",
# sep = "")))
## eval(parse(text = paste("K.",
# anthro,
# ".AbsBias <- c(
# eval(parse(text = paste(\"K.\", anthro, \".AbsBias\", sep = \"\"))),
# (fit$Parameters[3,1] - K.exp))",
# sep = "")))
}
noExclosureEstimates <- cbind(noExclosureEstimates,
eval(parse(text = paste("A.", anthro, ".N", sep = ""))),
eval(parse(text = paste("I.", anthro, ".N", sep = ""))),
eval(parse(text = paste("K.", anthro, ".N", sep = ""))))
}
noExclosureEstimates <- data.frame(noExclosureEstimates)
names(noExclosureEstimates) <- c("A.20", "I.20", "K.20",
"A.40", "I.40", "K.40",
"A.60", "I.60", "K.60")
write.csv(noExclosureEstimates, "output/fitAnalysis/noExclosureEstimates.csv",
row.names = FALSE)
#####################################
# Exclosure Estimate Generation
#####################################
dataExclosure <- treatmentData[ which(treatmentData$Excl.Rad == "Exclosure"), ]
exclosureEstimates <- NULL
for (anthro in unique(dataExclosure$Anthro))
{
eval(parse(text = paste("A.", anthro, ".E <- NULL", sep = "")))
eval(parse(text = paste("I.", anthro, ".E <- NULL", sep = "")))
eval(parse(text = paste("K.", anthro, ".E <- NULL", sep = "")))
# eval(parse(text = paste("A.", anthro, ".AbsBias <- NULL", sep = "")))
# eval(parse(text = paste("I.", anthro, ".AbsBias <- NULL", sep = "")))
# eval(parse(text = paste("K.", anthro, ".AbsBias <- NULL", sep = "")))
data <- dataExclosure[ which(dataExclosure$Anthro == anthro), ]
for (i in unique(data$Run))
{
dataTemp <- data[ which(data$Run == i), ]
fit <- nlsfit(dataTemp[c("Day", "Mean.Weight")], model=10, start=c(200,4,0.05))
#Push parameter estimates
eval(parse(text = paste("A.",
anthro,
".E <- c(
eval(parse(text = paste(\"A.\", anthro, \".E\", sep = \"\"))),
(fit$Parameters[1,1]))",
sep = "")))
eval(parse(text = paste("I.",
anthro,
".E <- c(
eval(parse(text = paste(\"I.\", anthro, \".E\", sep = \"\"))),
(fit$Parameters[2,1]))",
sep = "")))
eval(parse(text = paste("K.",
anthro,
".E <- c(
eval(parse(text = paste(\"K.\", anthro, \".E\", sep = \"\"))),
(fit$Parameters[3,1]))",
sep = "")))
#Push absolute bias, do we need this?
# eval(parse(text = paste("A.",
# anthro,
# ".AbsBias <- c(
# eval(parse(text = paste(\"A.\", anthro, \".AbsBias\", sep = \"\"))),
# (fit$Parameters[1,1] - A.exp))",
# sep = "")))
# eval(parse(text = paste("I.",
# anthro,
# ".AbsBias <- c(
# eval(parse(text = paste(\"I.\", anthro, \".AbsBias\", sep = \"\"))),
# (fit$Parameters[2,1] - I.exp))",
# sep = "")))
## eval(parse(text = paste("K.",
# anthro,
# ".AbsBias <- c(
# eval(parse(text = paste(\"K.\", anthro, \".AbsBias\", sep = \"\"))),
# (fit$Parameters[3,1] - K.exp))",
# sep = "")))
}
exclosureEstimates <- cbind(exclosureEstimates,
eval(parse(text = paste("A.", anthro, ".E", sep = ""))),
eval(parse(text = paste("I.", anthro, ".E", sep = ""))),
eval(parse(text = paste("K.", anthro, ".E", sep = ""))))
}
exclosureEstimates <- data.frame(exclosureEstimates)
names(exclosureEstimates) <- c("A.20", "I.20", "K.20",
"A.40", "I.40", "K.40",
"A.60", "I.60", "K.60")
write.csv(exclosureEstimates, "output/fitAnalysis/exclosureEstimates.csv",
row.names = FALSE)