smooth_lss: Smooth predicted polarity scores by local polynomial...

In koheiw/LSS: Semi-Supervised Algorithm for Document Scaling

Smooth predicted polarity scores by local polynomial regression

Description

Smooth predicted polarity scores by local polynomial regression

Usage

smooth_lss(
  x,
  lss_var = "fit",
  date_var = "date",
  span = 0.1,
  group = NULL,
  from = NULL,
  to = NULL,
  by = "day",
  engine = c("loess", "locfit"),
  ...
)

Arguments

x	a data.frame containing polarity scores and dates.
lss_var	the name of the column in x for polarity scores.
date_var	the name of the column in x for dates.
span	the level of smoothing.
group	the name of the column in x to smooth the data by group.
from, to, by	the the range and the internal of the smoothed scores; passed to seq.Date.
engine	specifies the function to be used for smoothing.
...	additional arguments passed to the smoothing function.

Details

Smoothing is performed using stats::loess() or locfit::locfit(). When the x has more than 10000 rows, it is usually better to choose the latter by setting engine = "locfit". In this case, span is passed to locfit::lp(nn = span).

koheiw/LSS documentation built on July 24, 2024, 6:31 p.m.