outlierCriteria.Rd
this function calculates outlier criteria on plants for each parameter
outlierCriteria( datain, typeD, residin, typeR, trait, resRawName, resStdName, threshold )
datain | input dataframe of parameters |
---|---|
typeD | type of datain dataframe (1==wide, 2==long) |
residin | input dataframe of residuals |
typeR | type of residin dataframe (1==wide, 2==long) |
trait | character, trait of interest to model (example biovolume24, PH24 ...) |
resRawName | character, names of the raw residual in datain |
resStdName | character, names of the standardized residual in datain |
threshold, | numeric threshold for the normal quantile in raw criteria |
a dataframe with columns identifiying criteria used to detect outlier plants with 1==plant OK - 0==plant KO to suppress
raw criterion, critci: quartiles criterion
influence criterion with standardized residuals
This function needs in input a dataframe with residuals extracted from a mixed linear model (for instance using asreml or nlme libraries) and an another dataframe with the estimated parameters (biovolume, plantHeight, leafArea etc...). Several criteria will be calculated using different types of residuals. The 2 input dataframe must contain the following columns names: "experimentAlias","Line" and "Position".
use raw residuals
uses standardized residuals
The function must be executed for each parameter of interest: biovolume, plantHeight and phy. Each criteria will be used according with some rules:
biovolume and phy
biovolume and plantHeight
# Not run # dt1<-outlierCriteria()