cosinor  R Documentation 
Fits a cosinor model as part of a generalized linear model.
cosinor( formula, date, data, family = gaussian(), alpha = 0.05, cycles = 1, rescheck = FALSE, type = "daily", offsetmonth = FALSE, offsetpop = NULL, text = TRUE )
formula 
regression formula. 
date 
a date variable if type=“daily”, or an integer between 1 and 53 if type=“weekly”, or an integer between 1 and 12 if type=“monthly”, or a POSIXct date if type=“hourly”. 
data 
data set as a data frame. 
family 
a description of the error distribution and link function to be used in the model. Available link functions: identity, log, logit, cloglog. Note, it must have the parentheses. 
alpha 
significance level, set to 0.05 (default). 
cycles 
number of seasonal cycles per year if type=“daily”, “weekly” or “monthly”; number of cycles per 24 hours if type=“hourly” 
rescheck 
plot the residual checks (TRUE/FALSE), see

type 
“daily” for daily data (default), or “weekly” for weekly data, or “monthly” for monthly data, or “hourly” for hourly data. 
offsetmonth 
include an offset to account for the uneven number of
days in the month (TRUE/FALSE). Should be used for monthly counts
(type=“monthly”) (with 
offsetpop 
include an offset for the population (optional), this should be a variable in the data frame. Do not logtransform this offset, as the transform is applied by the code. 
text 
add explanatory text to the returned phase value (TRUE) or
return a number (FALSE). Passed to the 
The cosinor model captures a seasonal pattern using a sinusoid. It is
therefore suitable for relatively simple seasonal patterns that are
symmetric and stationary. The default is to fit an annual seasonal pattern
(cycle
=1), but other higher frequencies are possible (e.g., twice per
year: cycle
=2). The model is fitted using a sine and cosine term that
together describe the sinusoid. These parameters are added to a generalized
linear model, so the model can be fitted to a range of dependent data (e.g.,
Normal, Poisson, Binomial). Unlike the nscosinor
model, the cosinor
model can be applied to unequally spaced data.
Returns an object of class “Cosinor” with the following parts:
call 
the original call to the cosinor function. 
glm 
an
object of class 
fitted 
fitted values for intercept and cosinor only (ignoring other independent variables). 
fitted.plus 
standard fitted values, including all other independent variables. 
residuals 
residuals. 
date 
name of the date variable (in Date format when type=‘daily’). 
Adrian Barnett a.barnett@qut.edu.au
Barnett, A.G., Dobson, A.J. (2010) Analysing Seasonal Health Data. Springer.
summary.Cosinor
, plot.Cosinor
## cardiovascular disease data (offset based on number of days in... ## ...the month scaled to an average month length) data(CVD) res = cosinor(cvd~1, date='month', data=CVD, type='monthly', family=poisson(), offsetmonth=TRUE) summary(res) seasrescheck(res$residuals) # check the residuals ## stillbirth data data(stillbirth) res = cosinor(stillborn~1, date='dob', data=stillbirth, family=binomial(link='cloglog')) summary(res) plot(res) ## hourly indoor temperature data res = cosinor(bedroom~1, date='datetime', type='hourly', data=indoor) summary(res) # to get the pvalues for the sine and cosine estimates summary(res$glm)
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