Extract the special/global features of a multiple component
cosinor. In a multiple component model, there are specific parameters that
are not within the model itself, but must be extracted from the model fit.
When extracted, can be used to improve the plot of a multiple component
cosinor. However, this is only possible if the cosinor is harmonic (see
details
). For single-component models, the orthophase is the same as the
acrophase and the global amplitude
Global Amplitude (Ag) = the overall amplitude is defined as half the difference between the peak and trough values
Orthophase (Po) = the lag until the peak time
Bathyphase (Pb) = the lag until the trough time
Arguments
- object
Model of class
cosinor
with multiple periods- population
If the object is a population cosinor, should the features be calculated for the individual cosinors or for the population-cosinors. Default is TRUE. This has no effect on "Individual" cosinor objects.
If TRUE, then will calculate features for entire population.
If FALSE, then will calculate features for every individual cosinor in the population.
- ...
For extensibility
Value
When returning the cosinor features for a single model, will return
an object of class list
. When returning the cosinor features for every
individual in a population cosinor, will return an object of class
tibble
.
Details
These calculations can only occur if the periods of the cosinor are harmonic - as in, the longest period is a integer multiple of the smallest period (known as the fundamental frequency). Otherwise, these statistics are not accurate or interpretable.
Examples
data(twins)
model <- cosinor(rDYX ~ hour, twins, c(24, 8), "patid")
#> 23 subjects were removed due to having insufficient observations.
results <- cosinor_features(model, population = FALSE)
#> This is a harmonic multiple-component cosinor object. The orthophase, bathyphase, and global amplitude were calculated.
head(results)
#> # A tibble: 6 × 7
#> population harmonic peak trough ampGlobal orthophase bathyphase
#> <dbl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 TRUE 3.35 1.81 0.768 23 12
#> 2 2 TRUE 3.05 2.25 0.398 3.71 15.9
#> 3 7 TRUE 2.96 2.30 0.330 10.4 23.0
#> 4 8 TRUE 4.23 2.41 0.909 13 1
#> 5 9 TRUE 2.64 2.19 0.222 9 21
#> 6 10 TRUE 3.85 2.50 0.671 14 2