Example output dataframe from function randwin.
Output file from function
randwin using temperature and mass data.
A data frame with 5 rows and 21 variables.
Difference between model AICc of fitted climate window and a null model containing no climate.
The start day of each tested climate window. Furthest from the biological record.
The end day of each tested climate window. Closest to the biological record.
Beta estimate of the relationship between temperature and mass.
Standard error term for linear model betas.
Quadratic beta estimate of the relationship between temperature and mass.
Cubic beta estimate of the relationship between temperature and mass.
The function used to fit climate (e.g. linear ("lin"), quadratic ("quad"))
Furthest day back considered in slidingwin.
Closest day back considered in slidingwin.
The aggregate statistic used to analyse climate (e.g. mean, max, slope).
Whether "fixed" or "variable" climate windows were tested.
Number of folds used for k-fold cross validation.
Model weight of each fitted climate window.
Sample size (i.e. number of years or sites) used for climate window analysis.
If type is "absolute", the date from which the climate window was tested.
Whether the data was generated using
The number of randomisations carried out.
Model spread of 95 percent confidence set of models.
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