R: Add a Confidence Region or Bayesian Credible Region for...

regcr {mixtools} | R Documentation

## Add a Confidence Region or Bayesian Credible Region for Regression Lines to a Scatterplot

### Description

Produce a confidence or credible region for regression lines based on a sample of bootstrap beta values or posterior beta values. The beta parameters are the intercept and slope from a simple linear regression.

### Usage

    regcr(beta, x, em.beta = NULL, em.sigma = NULL, alpha = .05,
          nonparametric = FALSE, plot = FALSE, xyaxes = TRUE, ...)

### Arguments

`beta` | An nx2 matrix of regression parameters. The first column gives the intercepts and the second column gives the slopes.
`x` | An n-vector of the predictor variable which is necessary when nonparametric = TRUE.
`em.beta` | The estimates for beta required when obtaining confidence regions. This is required for performing the standardization necessary when obtaining nonparametric confidence regions.
`em.sigma` | The estimates for the regression standard deviation required when obtaining confidence regions. This is required for performing the standardization necessary when obtaining nonparametric confidence regions.
`alpha` | The proportion of the beta sample to remove. In other words, 1-alpha is the level of the credible region.
`nonparametric` | If nonparametric = TRUE, then the region is based on the convex hull of the remaining beta after trimming, which is accomplished using a data depth technique. If nonparametric = FALSE, then the region is based on the asymptotic normal approximation.
`plot` | If plot = TRUE, lines are added to the existing plot. The type of plot created depends on the value of xyaxes.
`xyaxes` | If xyaxes = TRUE and plot = TRUE, then a confidence or credible region for the regression lines is plotted on the x-y axes, presumably overlaid on a scatterplot of the data. If xyaxes = FALSE and plot = TRUE, the (convex) credible region for the regression line is plotted on the beta, or intercept-slope, axes, presumably overlaid on a scatterplot of beta.
`...` | Graphical parameters passed to `lines` or `plot` command.

### Value

`regcr` returns a list containing the following items:

`boundary` | A matrix of points in beta, or intercept-slope, space arrayed along the boundary of the confidence or credible region.
`upper` | A matrix of points in x-y space arrayed along the upper confidence or credible limit for the regression line.
`lower` | A matrix of points in x-y space arrayed along the lower confidence or credible limit for the regression line.

### See Also

`regmixEM`, `regmixMH`

### Examples

    ## Nonparametric credible regions fit to NOdata.

    data(NOdata)
    attach(NOdata)
    set.seed(100)
    beta <- matrix(c(1.3, -0.1, 0.6, 0.1), 2, 2)
    sigma <- c(.02, .05)
    MH.out <- regmixMH(Equivalence, NO, beta = beta, s = sigma,
                       sampsize = 2500, omega = .0013)
    attach(data.frame(MH.out$theta))
    beta.c1 <- cbind(beta0.1[2400:2499], beta1.1[2400:2499])
    beta.c2 <- cbind(beta0.2[2400:2499], beta1.2[2400:2499])
    plot(NO, Equivalence)
    regcr(beta.c1, x = NO, nonparametric = TRUE, plot = TRUE,
          col = 2)
    regcr(beta.c2, x = NO, nonparametric = TRUE, plot = TRUE,
          col = 3)

[Package mixtools version 1.2.0 Index]