arse (version 1.0.0)

count_rapidity: Calculates a count of the time beneath the baseline.

Description

This function takes a series of y-coordinates and returns a count of y-coordinates that fall beneath the specified baseline after the intrusion of a stress event (i.e., rapidity).

Usage

count_rapidity(data, ycoord, ybase = NA, yinvert = FALSE,
  saveout = FALSE)

Arguments

data

A dataframe with x- and y-coordinates in wide format.

ycoord

A specified selection of the y-coordinate values within the dataframe. The first y-coordinate value should correspond to the baseline value of 'y'. The second y-coordinate value should be the first measure of 'y' after the intrusion of a stress event. The last value of 'y' should correspond to the last measurement of 'y' over the measured timeframe.

ybase

A specified selection of the baseline of the 'y' measured variable. Users are advised to place baseline as the first instance of the y-coordinate values. Function defaults to use the first y-coordinate value in the series.

yinvert

Specifies whether resilience occurs above or below the baseline depending on the meaning of high and low 'y' values. When parameter 'yinvert' is set to 'FALSE' (the default), it is assumed that higher numbers are indicative of positive (i.e., desired) 'y' values (e.g., exam grade). When 'yinvert' is set to 'TRUE', it is assumed that lower numbers are indicative of positive (i.e., desired) 'y' values (e.g., blood pressure).

saveout

When the parameter 'saveout' is set to 'FALSE' (the default), a vector of calculated count_rapidity values are given for each case. When 'saveout' is set to 'TRUE', a dataframe of the original inputted dataset is returned with a new column of calculated count_rapidity values.

Value

When the parameter 'saveout' is set to 'FALSE', a vector of calculated count_rapidity values are given for each case. When 'saveout' is set to 'TRUE', a dataframe of the original inputted dataset is returned with a new column of calculated count_rapidity values.

Examples

# NOT RUN {
xc <- t(c(1,2,3,4,5,6,7,8,9,10))
yc <- t(c(75,53,37,25,27,35,50,75,75,75))
dataset1 <- data.frame(xc, yc)
count_rapidity(data = dataset1, ycoord = dataset1[,11:20], saveout = TRUE)
# }