viscosity | R Documentation |
In an experimental setting the viscosity of resin was measured over time to asses the curing process depending on 5 binary factors (low-high).
data("viscosity")
A data list with 64 observations on the following 7 variables.
visAll
viscosity measures over all available time points
timeAll
time points of viscosity measures
T_C
temperature of tools
T_A
temperature of resin
T_B
temperature of curing agent
rspeed
rotational speed
mflow
mass flow
The aim is to determine factors that affect the curing process in the mold. The desired viscosity-curve has low values in the beginning followed by a sharp increase. Due to technical reasons the measuring method of the rheometer has to be changed in a certain range of viscosity. The first observations are measured by rotation of a blade giving observations every two seconds, the later observations are measured through oscillation of a blade giving observations every ten seconds. In the later observations the resin is quite hard so the measurements should be interpreted as a qualitative measure of hardening.
Wolfgang Raffelt, Technical University of Munich, Institute for Carbon Composites
data("viscosity", package = "FDboost")
## set time-interval that should be modeled
interval <- "101"
## model time until "interval" and take log() of viscosity
end <- which(viscosity$timeAll==as.numeric(interval))
viscosity$vis <- log(viscosity$visAll[,1:end])
viscosity$time <- viscosity$timeAll[1:end]
## fit median regression model with 100 boosting iterations,
## step-length 0.4 and smooth time-specific offset
## the factors are in effect coding -1, 1 for the levels
mod <- FDboost(vis ~ 1 + bols(T_C, contrasts.arg = "contr.sum", intercept=FALSE)
+ bols(T_A, contrasts.arg = "contr.sum", intercept=FALSE),
timeformula=~bbs(time, lambda=100),
numInt="equal", family=QuantReg(),
offset=NULL, offset_control = o_control(k_min = 9),
data=viscosity, control=boost_control(mstop = 100, nu = 0.4))
summary(mod)
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