| start_event | R Documentation |
Determine the starting point for each time series.
start_event( data, column = "Time", event = "Event", label = "start.event", label.event = NULL, order = TRUE, newcode = TRUE )
data |
A data frame. |
column |
Test string, name of the column that describes the order withing the time series. Default is 'Time'. |
event |
A text string or vector indicating the columns that define the unique time series. Default is 'Event'. |
label |
The name of the new column with the start point of each time series. Default is 'start.event'. |
label.event |
In case |
order |
Logical: whether or not to order each time series. Default is TRUE, maybe set to FALSE with large data frames that are already ordered. |
newcode |
Logical: whether or not to use the new (and hopefully faster) code. |
Data frame.
When working with large data frames, it may be worth installing the package
data.table. Although not required for the package, the function
start_event will check if data.table is available and will
use it's much faster function rbindlist. This speeds up the function
start_event. Run the command
install.packages('data.table', repos='http://cran.us.r-project.org')
in the command window for installing the package data.table.
Jacolien van Rij
Other functions for model criticism:
acf_n_plots(),
acf_plot(),
acf_resid(),
derive_timeseries(),
resid_gam(),
start_value_rho()
data(simdat)
head(simdat)
simdat <- simdat[sample(1:nrow(simdat)),]
simdat$Condition <- relevel(factor(simdat$Condition), ref="0")
contrasts(simdat$Condition) <- "contr.poly"
contrasts(simdat$Condition)
test <- start_event(simdat, event=c('Subject', 'Trial'), label.event='Event')
contrasts(test$Condition)
head(test)
test <- start_event(simdat, event="Subject")
test <- start_event(simdat, event=c('Subject', 'Trial'))
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