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cosinor()
unable to run on certain models based on y
valuescosinor_features()
allows for assessing global/special
attributes of multiple component cosinor analysisggcosinor()
is now functional for single and multiple
component analysisbuild_sequential_models()
, however it is in a list format
and will likely be updated to be more “tidy” in the futureggpopcosinor()
can show the cosinors for individuals
across a population, along with mean and predicted cosinorggcosinor()
accepts single modelsprint.cosinor()
and plot.cosinor()
functions addedcosinor_zero_amplitude()
test added, works for
individual cosinor.cosinor()
now takes the argument of for individuals. The individual cosinor
methods generally work, but may not yet be accurate.circ_compare_groups()
helps to summarize
circadian data by an covariate and time. This is visualized using
ggcircadian()
. Also includes the ggforest()
to
create forest plots of odds ratios. This is dependent on the
circ_odds()
function to generate odds ratios by time.hardhat
package from tidymodels,
cosinor()
introduced as a new function to allow for
diagnostic analysis of circadian patterns. Although the algorithm is
well known, having an implementation in R allows potential diagnostics.
This includes the ggcosinorfit()
allows for assessing
rhythmicity and confidence intervals of amplitude and acrophase of
cosinor model. Basic methods for assessing the model, such as
print
, summary
, coef
, and
confint
currently function.recur_survival_table()
, which allows for redesigning
longitudinal data tables into a model appropriate for analysis. It is
built to extend survival analyses. The
recur_summary_table()
function allows for reviewing the
findings from recurrent events by category to help understand event
strata.circ_sun()
function allows for identifying the
sunrise and sunset times based on geographical location. This is
intended to couple with the circ_center()
function to
center a time series around an event, such as sunrise. A vignette has
been added to review this data.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.