FDboost (version 1.0-0)

viscosity: Viscosity of resin over time

Description

In an experimental setting the viscosity of resin was measured over time to asses the curing process depending on 5 binary factors (low-high).

Usage

data("viscosity")

Format

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

Details

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.

Examples

# NOT RUN {
 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)

# }