fit_loess {metabCombiner} | R Documentation |
Fits a local regression smoothing spline through a set of ordered pair
retention times. modeling one set of retention times (rty) as a function
on the other set (rtx). Filtering iterations of high residual points are
performed first. Multiple acceptable values of span
can be used, with
one value selected through 10-fold cross validation.
fit_loess( object, useID = FALSE, spans = seq(0.2, 0.3, by = 0.02), iterFilter = 2, ratio = 2, frac = 0.5, iterLoess = 10, weights = 1 )
object |
metabCombiner object. |
useID |
logical. Option to use matched IDs to inform fit |
spans |
numeric span values (between 0 & 1) used for loess fits |
iterFilter |
integer number of residual filtering iterations to perform |
ratio |
numeric. A point is an outlier if the ratio of residual to mean residual of a fit exceeds this value. Must be greater than 1. |
frac |
numeric. A point is excluded if deemed a residual in more than this fraction value times the number of fits. Must be between 0 & 1. |
iterLoess |
integer. Number of robustness iterations to perform in
|
weights |
Optional user supplied weights for each ordered pair. Must be of length equal to number of anchors (n) or a divisor of (n + 2). |
metabCombiner
object with model
slot updated to
contain the fitted loess model
data(plasma30) data(plasma20) p30 <- metabData(plasma30, samples = "CHEAR") p20 <- metabData(plasma20, samples = "Red", rtmax = 17.25) p.comb = metabCombiner(xdata = p30, ydata = p20, binGap = 0.0075) p.comb = selectAnchors(p.comb, tolmz = 0.003, tolQ = 0.3, windy = 0.02) #version 1 p.comb = fit_loess(p.comb, spans = seq(0.2,0.3,0.02), iterFilter = 1) #version 2 (using weights) anchors = getAnchors(p.comb) weights = c(2, rep(1, nrow(anchors)), 2) #weight = 2 to boundary points p.comb = fit_loess(p.comb, spans = seq(0.2,0.3,0.02), weights = weights) #version 3 (using identities) p.comb = selectAnchors(p.comb, useID = TRUE, tolmz = 0.003) p.comb = fit_loess(p.comb, spans = seq(0.2,0.3,0.02), useID = TRUE) #to preview result of fit_loess plot(p.comb, fit = "loess", xlab = "CHEAR Plasma (30 min)", ylab = "Red-Cross Plasma (20 min)", pch = 19, main = "Example fit_loess Result Fit")