R: Fit Mean-Variance Trend by Local Regression

meanVarLocalFit {MAnorm2}

R Documentation

Fit Mean-Variance Trend by Local Regression

Description

meanVarLocalFit fits a mean-variance curve by applying a robust, gamma-family local regression.

Usage

meanVarLocalFit(
  x,
  y,
  weight,
  range.residual = c(1e-04, 15),
  max.iter = 50,
  args.lp = list(),
  args.locfit = list(),
  verbose = TRUE
)

Arguments

`x`, `y`	Two numeric vectors of (sample) means and sample variances, respectively.
`weight`	An optional vector of weights to be used in the fitting procedure. It's typically used when sample variances in `y` are associated with different numbers of degrees of freedom.
`range.residual`	A length-two vector specifying the range of residuals of non-outliers.
`max.iter`	Maximum number of iteration times allowed during the fitting procedure.
`args.lp`	A named list of extra arguments to `lp`.
`args.locfit`	A named list of extra arguments to `locfit`.
`verbose`	Whether to print processing messages about iteratively fitting the mean-variance curve?

Details

meanVarLocalFit iteratively detects outliers and applies the local regression procedure to non-outliers. The procedure converges as soon as the set of outlier points fixes.

Value

A prediction function which accepts a vector of means and returns the predicted variances.

Note

Due to the internal implementation, the argument subset to locfit mustn't be specified in args.locfit.