The parameter required to initialize the algorithm. Can be:
The floating-point type that the algorithm uses for intermediate computations. Can be
Available methods for computation of low order moments:
Estimates to be computed by the algorithm:
Step 1 - on Local Nodes
Pointer to the
pnumeric table that represents the
i-th data block on the local node.
While the input for
sumDensemethod can be an object of any class derived from
NumericTable, the input for
sumCSRmethod can only be an object of the
Pointer to the 1 x 1 numeric table that contains the number of observations processed so far on the local node. By default, this result is an object of the
HomogenNumericTableclass, but you can define the result as an object of any class derived from
Partial characteristics computed so far on the local node, each in a 1 x
pnumeric table. By default, each table is an object of the
HomogenNumericTableclass, but you can define the tables as objects of any class derived from
Partial sums of squares.
Partial sums of squared differences from the means.
Step 2 - on Master Node
A collection that contains numeric tables with partial results computed in Step 1 on local nodes (six numeric tables from each local node). These numeric tables can be objects of any class derived from the
Sums of squares.
Sums of squared differences from the means.
Estimates for the means.
Estimates for the second order raw moments.
Estimates for the variances.
Estimates for the standard deviations.
Estimates for the variations.
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Notice revision #20110804