Layer a smooth line for loon — l_layer

Display a smooth line layer

Usage

l_layer_smooth(
  widget,
  x = NULL,
  y = NULL,
  method = "loess",
  group = "",
  formula = y ~ x,
  interval = c("none", "confidence", "prediction"),
  n = 80,
  span = 0.75,
  level = 0.95,
  methodArgs = list(),
  linecolor = "steelblue",
  linewidth = 2,
  linedash = "",
  confidenceIntervalArgs = list(linecolor = "gray80", linewidth = 4, linedash = ""),
  predictionIntervalArgs = list(linecolor = "gray50", linewidth = 3, linedash = 1),
  label = "smooth",
  parent = "root",
  index = 0,
  ...
)

Arguments

widget: widget path name as a string
x: The x coordinates of line. If it is not provided, x will be inherited from widget
y: The y coordinates of line. If it is not provided, y will be inherited from widget
method: Smoothing method (function) to use, accepts either a character vector, e.g. "lm", "glm", "loess" or a function, e.g. MASS::rlm or mgcv::gam, stats::lm, or stats::loess.
group: Data can be grouped by n dimensional aesthetics attributes, e.g. "color", "size". In addition, any length n vector or data.frame is accommodated.
formula: Formula to use in smoothing function, eg. y ~ x, y ~ poly(x, 2), y ~ log(x)
interval: type of interval, could be "none", "confidence" or "prediction" (not for glm)
n: Number of points at which to evaluate smoother.
span: Controls the amount of smoothing for the default loess smoother. Smaller numbers produce wigglier lines, larger numbers produce smoother lines.
level: Level of confidence interval to use (0.95 by default).
methodArgs: List of additional arguments passed on to the modelling function defined by method.
linecolor: fitted line color.
linewidth: fitted line width
linedash: fitted line dash
confidenceIntervalArgs: the line color, width and dash for confidence interval
predictionIntervalArgs: the line color, width and dash for prediction interval
label: label used in the layers inspector
parent: group layer
index: index of the newly added layer in its parent group
...: additional state initialization arguments, see l_info_states

Examples

if(interactive()) {
# loess fit
p <- l_plot(iris, color = iris$Species)
l1 <- l_layer_smooth(p, interval = "confidence")
l_layer_hide(l1)

# the fits are grouped by points color
l2 <- l_layer_smooth(p, group = "color",
                     method = "lm")

# so far, all intervals are hidden
ls <- l_layer_getChildren(l2)
intervals <- l_layer_getChildren(l_create_handle(c(p,ls[3])))
ci <- l_create_handle(c(p,intervals[3]))
l_layer_show(ci)
# show prediction interval
pi <- l_create_handle(c(p,intervals[2]))
l_layer_show(pi)
# hide all
l_layer_hide(l2)

# Draw a fitted line based on a new data set
shortSepalLength <- (iris$Sepal.Length < 5)
l3 <- l_layer_smooth(p,
                     x = iris$Sepal.Length[shortSepalLength],
                     y = iris$Sepal.Width[shortSepalLength],
                     method = "lm",
                     linecolor = "firebrick",
                     interval = "prediction")
l_layer_hide(l3)

if(require(mgcv)) {
  # a full tensor product smooth
  ## linecolor is the same with the points color
  l4 <- l_layer_smooth(p,
                       method = "gam",
                       formula = y~te(x))
  l_layer_hide(l4)
}

# facets
fp <- l_facet(p, by = iris$Species, inheritLayers = FALSE)
l5 <- l_layer_smooth(fp, method = "lm")

# generalized linear model
if(require("loon.data")) {
  data("SAheart")
  # logit regression
  chd <- as.numeric(SAheart$chd) - 1
  age <- SAheart$age
  p1 <- l_plot(age, chd,
               title = "logit regression")
  gl1 <- l_layer_smooth(p1,
                        method = "glm",
                        methodArgs = list(family = binomial()),
                        interval = "conf")

  # log linear regression
  counts <- c(18,17,15,20,10,20,25,13,12)
  age <- c(40,35,53,46,20,33,48,25,23)
  p2 <- l_plot(age, counts,
               title = "log-linear regression")
  gl2 <- l_layer_smooth(p2,
                        method = "glm",
                        methodArgs = list(family = poisson()),
                        interval = "conf")
}
}