monthglm {season} | R Documentation |
Fit a generalized linear model with a categorical independent variable of month.
monthglm(formula,data,family=gaussian(),refmonth=1,offsetmonth=FALSE, offsetpop=NULL) ## S3 method for class 'monthglm': print(x, ...)
formula |
regression model formula, e.g., y~x1+x2 , (do not
add month to the regression equation, it will be added
automatically). |
data |
a data frame. |
family |
a description of the error distribution and link
function to be used in the model (default=gaussian() ). (See
family for details of family functions.). |
refmonth |
reference month, must be between 1 and 12 (default=1 for January). |
offsetmonth |
include an offset to account for the uneven number
of days in the month (TRUE/FALSE). Should be used for monthly counts
(with family=poisson() ). |
offsetpop |
include an offset for the population (optional), this should be a variable in the data frame. Do not log-transform the offset as the log-transform is applied by the function. |
x |
Object of class monthglm |
... |
further arguments passed to or from other methods. |
Month is fitted as an independent variable as part of a
generalized linear model. Other independent variables can be added to
the right-hand side of formula
.
This model is useful for examining non-sinusoidal seasonal
patterns. For sinusoidal seasonal patterns see cosinor
.
The data frame should contain the integer months in a variable called ‘month’.
call |
the original call to the monthglm function. |
fit |
GLM model. |
fitted |
fitted values. |
residuals |
residuals. |
out |
details on the monthly estimates. |
Adrian Barnett a.barnett<at>qut.edu.au
Barnett, A.G., Dobson, A.J. (2010) Analysing Seasonal Health Data. Springer.
summary.monthglm
, plot.monthglm
data(CVD) mmodel<-monthglm(formula=cvd~1,data=CVD,family=poisson(), offsetpop=pop/100000,offsetmonth=TRUE)