Description Usage Arguments Value Time-Series Phenotypes See Also
Infer time step of time-series phenotypes.
1 | inferTimeStep(cross, allow.gaps = TRUE, tol = 1e-05)
|
cross |
An R/qtl |
allow.gaps |
Allow gaps in time series, provided that any gaps are a multiple of the inferred time step. |
tol |
Tolerance for time step equality. |
Inferred time step. Returns NULL
if time step could not be inferred.
A set of phenotypes can be designated as a time-series by naming each
phenotype with the time point at which phenotype observations were made
(e.g. '0.0'
, '1.0'
, '2.0'
). Time points can be in
any unit, but must be non-negative, monotonically increasing, and have
a consistent time step. If some time points are missing, the resulting
gap in time must be a multiple of the time step.
Other cross object functions: crossesEqual
,
getIdColIndex
,
getPhenoColIndices
,
hasTimeSeriesPhenotypes
,
inferStrainIndices
,
inferTetradIndices
,
interpTimeSeries
,
padTimeSeries
, permCross
,
permIndices
, pull.alleles
,
pull.chr
, pull.crosstype
,
pull.ind
, readCrossCSV
,
readCrossHDF5
, writeCrossCSV
,
writeCrossHDF5
Other time-series functions: hasTimeSeriesPhenotypes
,
interpTimeSeries
,
padTimeSeries
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