mixregTrim function

Robust Regression Estimator Using Trimmed Likelihood

`mixregTrim' is used for robust regression estimation of a mixture model using the trimmed likelihood estimator (Neykov et al., 2007). It trims the data to reduce the impact of outliers on the model.

mixregTrim(x, y, C = 2, keep = 0.95, nstart = 20)

Arguments

• x: an n by p data matrix where n is the number of observations and p is the number of explanatory variables. The intercept term will automatically be added to the data.
• y: an n-dimensional vector of response variable.
• C: number of mixture components. Default is 2.
• keep: proportion of data to be kept after trimming, ranging from 0 to 1. Default is 0.95.
• nstart: number of initializations to try. Default is 20.

Returns

A list containing the following elements: - pi: C-dimensional vector of estimated mixing proportions.

• beta: C by (p + 1) matrix of estimated regression coefficients.

• sigma: C-dimensional vector of estimated standard deviations.

• lik: final likelihood.

Examples

data(tone)
y = tone$tuned
x = tone$stretchratio
k = 160
x[151:k] = 0
y[151:k] = 5
est_TLE = mixregTrim(x, y, 2, 0.95, nstart = 1)

References

Neykov, N., Filzmoser, P., Dimova, R., and Neytchev, P. (2007). Robust fitting of mixtures using the trimmed likelihood estimator. Computational Statistics & Data Analysis, 52(1), 299-308.