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).
monthvar: name of the month variable which is either an integer (1 to 12) or a character or factor (Jan' to Dec' or January' to December') (default='month').
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.
Returns
call: the original call to the monthglm function.
fit: GLM model. - fitted: fitted values.
residuals: residuals. - out: details on the monthly estimates.
Details
Month is fitted as a categorical 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 and the year as a 4 digit number. These are used to calculate the number of days in each month accounting for leap years.