SPCModellm: Data model based on a linear model

In spcadjust: Functions for Calibrating Control Charts

Description

The parameters needed for running the chart are the fitted linear model. Resampled data sets are created by resampling cases with replacement (i.e. keeping observations together).

Usage

SPCModellm(formula, Delta = 0)

Arguments

formula	the linear model specified as a formula.
Delta	Object of class "numeric".

Examples

n <- 1000
Xlinreg <- data.frame(x1= rbinom(n,1,0.4), x2= runif(n,0,1), x3= rnorm(n))
Xlinreg$y <- 2 + Xlinreg$x1 + Xlinreg$x2 + Xlinreg$x3 + rnorm(n)
## Not run: 
chartlinregCUSUM <- new("SPCCUSUM", model=SPCModellm(Delta=1,formula="y~x1+x2+x3"))
SPCproperty(data=Xlinreg,nrep=10,property="calARL",
            chart=chartlinregCUSUM,params=list(target=100))
#increase nrep in real applications.
#' chartlinregCUSUM2 <- new("SPCCUSUM",model=SPCModellm(Delta=1,formula="y~x1"))
SPCproperty(data=Xlinreg,nrep=10,property="calARL",
            chart=chartlinregCUSUM2,params=list(target=100))
#increase nrep in real applications.

chartlinregEWMA <- new("SPCEWMA", model=SPCModellm(Delta=0,formula="y~x1+x2+x3"),lambda=0.8)
SPCproperty(data=Xlinreg,nrep=10,property="calARL",
            chart=chartlinregEWMA,params=list(target=100))
#increase nrep in real applications.

chartlinregEWMA2 <- new("SPCEWMA",model=SPCModellm(Delta=0,formula="y~x1"),lambda=0.8)
SPCproperty(data=Xlinreg,nrep=10,property="calARL",
            chart=chartlinregEWMA2,params=list(target=100))

## End(Not run)
#increase nrep in real applications.

spcadjust documentation built on May 1, 2019, 7:49 p.m.