Simulated w0 data used in Murray et al. (2013)

Description

This data set gives simulated data from the function

y = 0.1x^3 + e

for e ~ N(0,0.01^2) and x evenly spaced between -1 and 1.

Format

A data frame with 21 observations on the following 2 variables.

y

a numeric vector

x

a numeric vector

Source

Murray, K., M<c3><83><c2><bc>ller, S. and Turlach, B.A. (2013). Revisiting fitting monotone polynomials to data, Computational Statistics 28(5): 1989–2005. Doi:10.1007/s00180-012-0390-5.

Examples

str(w0)
plot(y~x, w0)
monpol(y~x, w0)

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(MonoPoly)
Loading required package: quadprog
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MonoPoly/w0.Rd_%03d_medium.png", width=480, height=480)
> ### Name: w0
> ### Title: Simulated w0 data used in Murray et al. (2013)
> ### Aliases: w0
> ### Keywords: datasets
> 
> ### ** Examples
> 
> str(w0)
'data.frame':	21 obs. of  2 variables:
 $ y: num  -0.0847 -0.0598 -0.042 -0.0397 -0.0299 ...
 $ x: num  -1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 ...
> plot(y~x, w0)
> monpol(y~x, w0)

Monotone polynomial model
Call:
monpol(formula = y ~ x, data = w0)

Coefficients:
    beta0      beta1      beta2      beta3  
-0.004059   0.015497   0.008259   0.072618  

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>