TREND

TREND estimates future values of a given data set using a least squares approximation

Synopsis

TREND(known_ys,known_xs,new_xs,affine)

Arguments

known_ys: vector of values of dependent variable

known_xs: array of values of independent variables, defaults to a single vector {1,…,n}

new_xs: array of x-values for which to estimate the y-values; defaults to known_xs

affine: if true, the model contains a constant term, defaults to true

Note

If the length of known_ys does not match the corresponding length of known_xs, this function returns a #NUM! error.

See also

LINEST.