Example output dataframe from function slidingwin.

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Description

Output file from slidingwin using temperature and body mass data. Generated with Mass and MassClimate dataframes.

Format

A data frame with 5,151 rows and 19 variables.

deltaAICc

Difference between model AICc of fitted climate window and a null model containing no climate.

WindowOpen

The start day of each tested climate window. Furthest from the biological record.

WindowClose

The end day of each tested climate window. Closest to the biological record.

ModelBeta

Beta estimate of the relationship between temperature and mass.

Std.Error

Standard error term for linear model betas.

ModelBetaQ

Quadratic beta estimate of the relationship between temperature and mass.

ModelBetaC

Cubic beta estimate of the relationship between temperature and mass.

ModelInt

Model intercept.

Function

The function used to fit climate (e.g. linear ("lin"), quadratic ("quad"))

Furthest

Furthest day back considered in slidingwin.

Closest

Closest day back considered in slidingwin.

Statistics

The aggregate statistic used to analyse climate (e.g. mean, max, slope).

Type

Whether "absolute" or "relative" climate windows were tested.

K

Number of folds used for k-fold cross validation.

ModWeight

Model weight of each fitted climate window.

sample.size

Sample size (i.e. number of years or sites) used for climate window analysis.

Reference.day,Reference.month

If type is "absolute", the date from which the climate window was tested.

Randomised

Whether the data was generated using slidingwin or randwin.

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