Get salinity/flow normalized WRTDS predictions from interpolation grids
Get salinity/flow normalized WRTDS predictions from interpolation grids
Get normalized model predictions from WRTDS to remove the effect of salinity/flow on the response variable. Predicted values in the interpolation grids are averaged across dates.
resnorm(dat_in,...)## S3 method for class 'tidal'resnorm(dat_in, trace =TRUE,...)## S3 method for class 'tidalmean'resnorm(dat_in, trace =TRUE,...)
Arguments
dat_in: input tidal or tidalmean object
...: arguments passed to or from other methods
trace: logical indicating if progress is shown in the console
Returns
Appends columns to the data.frame for normalized values. For, tidal objects, columns are named starting with the prefix norm', e.g., norm0.5' are the normalized values for the fit through the median. For tidalmean objects, columns are appended for the log-transformed and back-transformed normalized values, named norm' and bt_norm'.
Details
This function is used after wrtds to normalize predicted values of the response variable from the interpolation grid for each model. The normalized values are based on the average of all predicted estimates across the range of salinity/flow values that have occurred on the same date throughout each year. For example, normalized values for July 2000 are the mean predicted response at that date using the observed salinity/flow values that occur in July of all years. The normalized values allow an interpretation of trends in the response variable that are independent of changes in salinity or freshwater inputs.
Examples
## Not run:### load a tidal objectdata(tidobj)# get flow-normalized values for each quantileres <- resnorm(tidobj)# load a tidalmean objectdata(tidobjmean)# get flow-normalized valuesres <- resnorm(tidobjmean)## End(Not run)