cvPCR {ldsr} | R Documentation |
Cross validation of PCR reconstruction.
Description
Cross validation of PCR reconstruction.
Usage
cvPCR(
Qa,
pc,
start.year,
transform = "log",
Z = NULL,
metric.space = "transformed"
)
Arguments
Qa |
Observations: a data.frame of annual streamflow with at least two columns: year and Qa. |
pc |
For a single model: a data.frame, one column for each principal component. For an ensemble reconstruction: a list, each element is a data.frame of principal components. |
start.year |
Starting year of the climate proxies, i.e, the first year of the paleo period. |
transform |
Flow transformation, either "log", "boxcox" or "none". Note that if the Box-Cox transform is used, the confidence interval after back-transformation is simply the back-transform of the trained onfidence interval; this is hackish and not entirely accurate. |
Z |
A list of cross-validation folds. If |
metric.space |
Either "transformed" or "original", the space to calculate the performance metrics. |
Value
A list of cross validation results
metrics.dist: distribution of performance metrics across all cross-validation runs; a matrix, one column for each metric, with column names.
metrics: average performance metrics; a named vector.
obs: the (transformed) observations, a data.table with two columns (year, y)
Ycv: the predicted streamflow in each cross validation run; a matrix, one column for each cross-validation run
Z: the cross-validation fold
Examples
cvPCR(NPannual, NPpc, start.year = 1200)