This function calculates the cumulative non-visual direct response (nvRD). This is basically the integral of the nvRD over the provided time period in hours. The unit of the resulting value thus is "nvRD*h".
Arguments
- nvRD
Numeric vector containing the non-visual direct response. See
nvRD
.- Time.vector
Vector containing the time data. Can be POSIXct, hms, duration, or difftime.
- epoch
The epoch at which the data was sampled. Can be either a duration or a string. If it is a string, it needs to be either
"dominant.epoch"
(the default) for a guess based on the data, or a valid duration string, e.g.,"1 day"
or"10 sec"
.- as.df
Logical. Should a data frame with be returned? If
TRUE
, a data frame with a single column namednvRD_cumulative
will be returned. Defaults toFALSE
.
References
Amundadottir, M.L. (2016). Light-driven model for identifying indicators of non-visual health potential in the built environment [Doctoral dissertation, EPFL]. EPFL infoscience. doi:10.5075/epfl-thesis-7146
See also
Other metrics:
bright_dark_period()
,
centroidLE()
,
disparity_index()
,
duration_above_threshold()
,
exponential_moving_average()
,
frequency_crossing_threshold()
,
interdaily_stability()
,
intradaily_variability()
,
midpointCE()
,
nvRC()
,
nvRD()
,
period_above_threshold()
,
pulses_above_threshold()
,
threshold_for_duration()
,
timing_above_threshold()
Examples
dataset1 <-
tibble::tibble(
Id = rep("A", 60 * 24),
Datetime = lubridate::as_datetime(0) + lubridate::minutes(0:(60*24-1)),
Illuminance = c(rep(0, 60*8), rep(sample(1:1000, 14, replace = TRUE), each = 60), rep(0, 60*2)),
MEDI = Illuminance * rep(sample(0.5:1.5, 24, replace = TRUE), each = 60)
) %>%
dplyr::mutate(
nvRD = nvRD(MEDI, Illuminance, Datetime)
)
dataset1 %>%
dplyr::summarise(
"cumulative nvRD" = nvRD_cumulative_response(nvRD, Datetime)
)
#> # A tibble: 1 × 1
#> `cumulative nvRD`
#> <dbl>
#> 1 8.72