normalize_to_first_timepoint: Normalize a time-indexed vector of values its first value.

In wfforrest/maeve: Modeling Accessories Enabling Visualization of Experiments

Description

From a data.frame, extract a y-vector of responses and their x-vector of observation times. Normalize the y-vector to its first (based on the x-values) observation, subtract out the centering value from the entire normalized vector, and return the normalized, centered vector.

Usage

normalize_to_first_timepoint(
  DATA_FRAME,
  x_name = "x",
  y_name = "y",
  average_multiple_obs = TRUE,
  centering_value = 1,
  scale_value = 100
)

Arguments

DATA_FRAME	data.frame with x-values (i.e, time-values) and y-values (responses.
x_name	character string with name of time value that order the responses.
y_name	character string with name of responses to be normalized to their own temporal baseline value.
average_multiple_obs	logical should we allow averaging of multiple baseline values, or call an error?
centering_value	numeric value to subtract from the normalized vector.
scale_value	numeric value by which to re-scale the normalized, centered vector.

Value

A numeric vector with normalized values.

Author(s)

Bill Forrest <[e-mail]>

Bill Forrest [e-mail]

References

www.r-project.org

Examples

normalizing_test_data <- data.frame( x = seq(0,1,length = 11) )
normalizing_test_data$y <- 1 + 2 * exp(-normalizing_test_data$x)
normalized_output <-
  data.frame( normalizing_test_data,
              y_norm = maeve:::normalize_to_first_timepoint( normalizing_test_data )
             )

wfforrest/maeve documentation built on Jan. 1, 2021, 12:47 p.m.