tests/test_sine.R

In hoangtt1989/NOIS: Non-parametric Outlier Identification and Smoothing

# library(NOIS)
#
# set.seed(123)
# npts <- 50
# nout <- floor(.1*npts)
#
# xt <- seq(from=0, to=2*pi, length.out=npts)
# gaussnoise <- rnorm(npts)
#
# outliers <- sample(floor(npts/2):npts, size=nout)
# randpts <- runif(nout, min=5, max=7)
# yt <- sin(xt) + gaussnoise
# yt[outliers] <- yt[outliers] + randpts
# xt_outliers = xt[outliers]
#
# orig_func <- sin(xt)
# data <- data.frame(x=xt, y=yt)
#
# fit <- NOIS_fit(data, CV_method = 'MCV')
# fit
# outlier_plot(fit)
#
# opt_BIC <- BIC_tuner(data)
# opt_fit <- opt_BIC$opt_fit
# opt_fit
# microbenchmark::microbenchmark(
#   NOIS_fit_lapply(data, CV_method = 'MCV'),
#   NOIS_fit_loop(data, CV_method = 'MCV')
# )

# # fit$conv$time
# # fit$local_q
# outlier_plot(fit)
# length(intersect(fit$pool_outlier, outliers))
# EL <- NOIS_confint(fit, conf_type = "EL", right = 2)
# EL$up_predicted > EL$low_predicted