Description Usage Arguments Details Value Examples
Convert original observations to emprical cdf
1 2 | get.cat.xy(x.ori, y.ori, n.missing, miss.sym = 0, top.missing = TRUE,
multi.fac = 1e-04)
|
x.ori |
replicate 1 : a vector of values from original observation |
y.ori |
replicate 2 : paired with |
n.missing |
the number of observations that miss both |
miss.sym |
the numerical symbol to represent a missing observation. It needs to be smaller than the smallest observed value. |
top.missing |
if missing value is present, |
multi.fac |
the cdf on the left side of the lower boundary of the bins |
Convert (x, y)
from original observations to emprical cdf and unique pairs.
cat.xy: a data.frame with nrow
= number of unique combinations of (x, y)
.
It has the following columns:
x, y: original values, only unique combinations to define a category.
factor.x, factor.y: level of factors, only unique values.
x.cdf, y.cdf: empirical cdf for each category, this is the upper boundary.
x.cdf.lo, y.cdf.lo: empirical cdf for each category, lower boundary.
(i.e. previous upper boundary). To avoid instability at boundary, the lowest x.cdf.lo
(y.cdf.lo
) is
1/(n.xy+1)
and the highest x.cdf
(y.cdf
) is n.xy/(n.xy+1)
.
m: number of observations in each category.
level.factor: can be used for mapping category format back to original
e.g. x.cat[level.factor[1]] == x[1], y.cat[level.factor[1]]==y[1]
.
1 2 3 4 |
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