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Performs quantile regressions of a dependent variable on factors estimates.
compute_fars(dep_variable, factors, h = 1, edge = 0.05)
An object of class fars, which is a list containing:
fars
models
List of five S3 quantreg::rq fitted objects named tau_0.xx.
quantreg::rq
tau_0.xx
h
The forecast horizon used.
levels
The vector of quantile levels effectively estimated (c(edge, 0.25, 0.50, 0.75, 1 - edge)).
c(edge, 0.25, 0.50, 0.75, 1 - edge)
.
periods
Integer. The number of fitted periods
n_factors
Integer. The number of factors included in the regression.
call
The matched function call.
Numeric vector of length T representing the dependent variable (e.g., GDP growth, inflation).
Numeric matrix or data frame of dimension T x r, containing factor estimates.
Integer (>= 1). Lag order used in the regression (default = 1)
Numeric value specifying the trimming amount applied to the outermost quantiles. Default is 0.05.
set.seed(123) T <- 100; r <- 3 Y <- rnorm(T) F <- matrix(rnorm(T * r), T, r) fars_result <- compute_fars(dep_variable = Y, factors = F, h = 1, edge = 0.05)
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