Specify a Unimodal Category in a CHANGEPT Formula

Description

A symbolic routine to define that the underlying mean curve is unimodal, i.e., it has a turn-around point, in the formula argument to changept.

Usage

tp(x, sh = 1)

Arguments

Value

"tp" returns the vector "x" with three attributes, i.e., nm: the name of x; categ: the category of the change-point, "mode"; sh: the shape constraint on the estimated curve: 1 (increasing-decreasing) or -1 (decreasing-increasing).

The nm and categ attributes are used in the plot routine; the sh attribute is used to set up a shape-constrained regression.

Author(s)

Xiyue Liao

See Also

ip, jp

Examples

  # the underlying mean curve is unimodal with a mode at .8 
  n = 100
  x = seq(1/n, 1, length = n)

  # a categorical covariate z with two levels (0 and 1) 
  z = rep(0:1, 50)

  set.seed(123)
  y = 30 * x^4 * (1 - x) + (z == 1) * .5 + rnorm(n, sd = 1)
  ans = changept(y ~ tp(x) + factor(z), family = gaussian())

  plot(ans)
  legend("topleft", "constrained fit for z == 1", bty = "n", col = "skyblue", lty = 2, lwd = 2)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(ShapeChange)
Loading required package: coneproj
Loading required package: quadprog
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ShapeChange/tp.Rd_%03d_medium.png", width=480, height=480)
> ### Name: tp
> ### Title: Specify a Unimodal Category in a CHANGEPT Formula
> ### Aliases: tp
> ### Keywords: symbolic routine
> 
> ### ** Examples
> 
>   # the underlying mean curve is unimodal with a mode at .8 
>   n = 100
>   x = seq(1/n, 1, length = n)
> 
>   # a categorical covariate z with two levels (0 and 1) 
>   z = rep(0:1, 50)
> 
>   set.seed(123)
>   y = 30 * x^4 * (1 - x) + (z == 1) * .5 + rnorm(n, sd = 1)
>   ans = changept(y ~ tp(x) + factor(z), family = gaussian())
> 
>   plot(ans)
>   legend("topleft", "constrained fit for z == 1", bty = "n", col = "skyblue", lty = 2, lwd = 2)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>