inst/scripts/Rumford_1.R

In ArkaB-DS/nlsCompare: Compare the best parameter values and sum-of-squares involved in solving nonlinear least squares (nls)

# NLSProbName: Rumford_1.R
# NLSProbDescription: {The Rumford data frame has 13 rows and 2 columns from an experiment by Count Rumford on the
# rate of cooling.
# The two columns are:This data frame contains the following columns:
# `time`:  a numeric vector giving the time since the beginning of the experiment (hr)
# `temp`:  a numeric vector giving the temperature (degrees Fahrenheit) of the cannon.
# The model has just 1 parameter.}

# Use the Rumford data from NRAIA package
## DATA
time <- c(4.0,  5.0,  7.0, 12.0, 14.0, 16.0, 20.0, 24.0, 28.0, 31.0, 34.0, 37.5, 41.0)
temp <- c(126, 125, 123, 120, 119, 118, 116, 115, 114, 113, 112, 111, 110)

NLSdata <- data.frame(time,temp)

## STARTING VALUE
tc = -0.01
NLSstart <- list(tc = tc) # a starting vector (named!)

## MODEL
NLSformula <-temp ~ 60 + 70 * exp(tc * time)
NLSlower<- c(-Inf)
NLSupper<- c(Inf)
NLSweights <- rep(1, length(time))
NLSsubset<-1:length(time)
NLSref<-"nlsr"
#NLSrefVersion<-packageVersion(NLSref)
refsol<-nlsr::nlxb(NLSformula,NLSstart,NLSdata,lower=NLSlower, upper=NLSupper,trace=TRUE)
NLSproblems <- read.table(system.file("extdata","problems.csv",
                                        package="nlsCompare"),header=TRUE,sep=",")
NLSpars<-as.numeric(subset(NLSproblems,Name=="Rumford_1.R")[4:(4+subset(NLSproblems,Name=="Rumford_1.R")$nPars-1)])
NLSssquares<-subset(NLSproblems,Name=="Rumford_1.R")$ssquares
NLStag<-"unbounded"
# NLSproblems[NLSproblems[,"Name"]=="Rumford_1.R",]$PkgVers<-paste(NLSref,NLSrefVersion,sep=":")
# NLSproblems[NLSproblems[,"Name"]=="Rumford_1.R",]$LastUpdated<-format(Sys.time(), "%Y-%m-%d %H:%M")
# write.table(NLSproblems,system.file("extdata","problems.csv",
#                                         package="nlsCompare"),append=FALSE,sep=",",col.names=FALSE,row.names=FALSE)
rm(time,temp,tc)