Evaluates one or several polynomials on the given data.
eval_poly(poly, newdata)
Returns a matrix containing the evaluation of the polynomials. Each column corresponds to each polynomial used and each row to each observation, meaning that each column vector corresponds to the results of evaluating all the given data for each polynomial.
List containing 2 items: labels
and values
.
labels
: List of integer vectors with same length (or number of cols)
as values
, where each integer vector denotes the combination of
variables associated to the coefficient value stored at the same position in
values
. That is, the monomials in the polynomial. Note that the
variables are numbered from 1 to p, with the intercept is represented by 0.
values
: Matrix (can also be a vector if single polynomial), where
each column represents a polynomial, with same number of rows as the length
of labels
, containing at each row the value of the coefficient
of the monomial given by the equivalent label in that same position.
Example: If labels
contains the integer vector c(1,1,3) at position
5, then the value stored in values
at row 5 is the coefficient
associated with the term x_1^2*x_3.
Input data as matrix, vector or dataframe. Number of columns (or elements in vector) should be the number of variables in the polynomial (dimension p). Response variable to be predicted should not be included.
Note that this function is unstable and subject to change. Therefore it is
not exported but this documentations is left available so users can use it if
needed to simulate data by using nn2poly:::eval_poly()
eval_poly()
is also used in predict.nn2poly()
.