runRegressions: Run regressions on a booking Matrix
In bookMatrix: Model to build a booking matrix and analyze it

Description Usage Arguments Details Value Examples

View source: R/bookMatrix.R

Run linear regressions on a cumulative hotel booking matrix

1
2
3

runRegressions(data1, lag, year1=2016, year2=2015, 
                oneyear=TRUE, wdayyes=TRUE, monthyes=TRUE, bayernholiday=TRUE,  publicholiday=TRUE,
                italholiday=FALSE, season=FALSE, season2=FALSE, clear=FALSE, ...)

`data1`	a data.frame with the variables target (contains bookings on arrival date), a undefined number of lags (contains bookings at the days before arrival) and undefined number of control variables.
`lag`	number of lag regressed on
`year1`	The year regressed on
`year2`	Year that is used for the comparison for the same date years before
`oneyear`	If `TRUE` add normalized one year ago on the same date data
`wdayyes`	If `TRUE` add weekdays in regression
`monthyes`	If `TRUE` add month in regression
`bayernholiday`	If `TRUE` add holidays in Bayern in regression
`publicholiday`	If `TRUE` add public holidays in Germany in regression
`italholiday`	If `TRUE` add holidays in Italy in regression
`season`	If `TRUE` add regular season in regression
`season2`	If `TRUE` add shorter season in regression
`clear`	If `TRUE` short output just inlcuding formula, the first coefficients and the rsquared
`...`	arguments to be used to form the default `control` argument if it is not supplied directly.

runRegressions run linear regressions on a cumulative hotel booking matrix

An object of class "lm.fit".

##create data
cBM2016 <- data.frame(a <- rnorm(n=30,mean=15), b <- rnorm(n=30,mean=10), b <- rnorm(n=30,mean=10))
colnames(cBM2016) <-  c("target", "lag5", "lagp5")

## use function with sample cBM2016
runRegressions(data1=cBM2016, lag=5, year1=2016, year2=2015, 
                oneyear=FALSE, wdayyes=FALSE, monthyes=FALSE, bayernholiday=FALSE, publicholiday=FALSE,
                italholiday=FALSE, season=FALSE, season2=FALSE, clear=FALSE)