palaeodataLagged: Lagged data generated by 'prepareLaggedData'.

In memoria: Quantifying Ecological Memory in Palaeoecological Datasets and Other Long Time-Series

Lagged data generated by prepareLaggedData.

Description

A dataframe resulting from the application of prepareLaggedData to the dataset palaeodata. The dataframe columns are named using the pattern VariableName__LagValue:

Usage

data(palaeodataLagged)

Format

dataframe with 19 columns and 3988 rows.

Details

• pollen.pinus__0 numeric, values of the response variable (pollen counts of Pinus) at lag 0 (current time). This column is used as the response variable by computeMemory.

• pollen.pinus__0.2-1 numeric, time-delayed values of the response for lags 0.2 to 1 (in ky). These columns represent the endogenous ecological memory.

• climate.temperatureAverage__0 numeric, temperature values at lag 0 (concurrent effect).

• climate.rainfallAverage__0 numeric, rainfall values at lag 0 (concurrent effect).

• climate.temperatureAverage__0.2-1 numeric, time-delayed temperature values for lags 0.2 to 1 (exogenous memory).

• climate.rainfallAverage__0.2-1 numeric, time-delayed rainfall values for lags 0.2 to 1 (exogenous memory).

• time numeric, the time/age column.

The dataframe has attributes response and drivers that are automatically used by computeMemory.

Author(s)

Blas M. Benito <[e-mail]>

See Also

Other example_data: climate, palaeodata, palaeodataMemory, pollen

memoria documentation built on Feb. 10, 2026, 9:07 a.m.