allNonZero: Returns a Reducer that returns 1 if all of its
inputs are non-zero, 0 otherwise.
anyNonZero: Returns a Reducer that returns 1 if any of its
inputs are non-zero, 0 otherwise.
bitwiseAnd: Returns a Reducer that computes the bitwise-and
summation of its inputs.
bitwiseOr: Returns a Reducer that computes the bitwise-or
summation of its inputs.
count: Returns a Reducer that computes the number of
non-null inputs.
first: Returns a Reducer that returns the first of its inputs.
firstNonNull: Returns a Reducer that returns the first of
its non-null inputs.
kurtosis: Returns a Reducer that Computes the kurtosis of
its inputs.
last: Returns a Reducer that returns the last of its inputs.
lastNonNull: Returns a Reducer that returns the last of its
non-null inputs.
max: Creates a reducer that outputs the maximum value of
its (first) input. If numInputs is greater than one, also outputs the
corresponding values of the additional inputs.
mean: Returns a Reducer that computes the (weighted)
arithmetic mean of its inputs.
median: Create a reducer that will compute the median of
the inputs. For small numbers of inputs (up to maxRaw) the median will be
computed directly; for larger numbers of inputs the median will be derived
from a histogram.
min: Creates a reducer that outputs the minimum value
of its (first) input. If numInputs is greater than one, also outputs
additional inputs.
mode: Create a reducer that will compute the mode of the
inputs. For small numbers of inputs (up to maxRaw) the mode will be
computed directly; for larger numbers of inputs the mode will be derived
from a histogram.
product: Returns a Reducer that computes the product of
its inputs.
sampleStdDev: Returns a Reducer that computes the sample
standard deviation of its inputs.
sampleVariance: Returns a Reducer that computes the sample
variance of its inputs.
stdDev: Returns a Reducer that computes the standard
deviation of its inputs.
sum: Returns a Reducer that computes the (weighted) sum
of its inputs.
variance: Returns a Reducer that computes the variance
of its inputs.