In an experimental setting the viscosity of resin was measured over time to asses the curing process depending on 5 binary factors (low-high).
A data list with 64 observations on the following 7 variables.
viscosity measures over all available time points
time points of viscosity measures
temperature of tools
temperature of resin
temperature of curing agent
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
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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] # with(viscosity, funplot(time, vis, pch=16, cex=0.2)) ## 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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