weights_almon: Compute Almon polynomials

In sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

Description

Computes Almon polynomial weighting curves. Handy to self-select specific time aggregation weighting schemes for input in ctr_agg using the weights argument.

Usage

weights_almon(n, orders = 1:3, do.inverse = TRUE, do.normalize = TRUE)

Arguments

n	a single numeric to indicate the lag length (cf., n).
orders	a numeric vector as the sequence of the Almon orders (cf., r). The maximum value corresponds to R.
do.inverse	TRUE if the inverse Almon polynomials should be calculated as well.
do.normalize	a logical, if TRUE weights are normalized to unity.

Details

The Almon polynomial formula implemented is: (1 - (1 - i/n)^r) * (1 - i/n)^(R - r), where i is the lag index ordered from 1 to n. The inverse is computed by changing i/n to 1 - i/n.

Value

A data.frame of all Almon polynomial weighting curves, of size length(orders) (times two if do.inverse = TRUE).

See Also

ctr_agg

sentometrics documentation built on Aug. 18, 2021, 9:06 a.m.