imputeLinInterpol {xcms} | R Documentation

## Impute values for empty elements in a vector using linear interpolation

### Description

This function provides missing value imputation based on linear interpolation and resembles some of the functionality of the `profBinLin` and `profBinLinBase` functions deprecated from version 1.51 on.

### Usage

    imputeLinInterpol(x, baseValue, method = "lin", distance = 1L,
      noInterpolAtEnds = FALSE)

### Arguments

`x` | A numeric vector with eventual missing (`NA`) values.
`baseValue` | The base value to which empty elements should be set. This is only considered for `method = "linbase"` and corresponds to the `profBinLinBase`'s `baselevel` argument.
`method` | One of `"none"`, `"lin"` or `"linbase"`.
`distance` | For `method = "linbase"`: number of non-empty neighboring element of an empty element that should be considered for linear interpolation. See details section for more information.
`noInterpolAtEnds` | For `method = "lin"`: Logical indicating whether linear interpolation should also be performed at the ends of the data vector (i.e. if missing values are present at the beginning or the end of the vector).

### Details

Values for NAs in input vector `x` can be imputed using methods `"lin"` and `"linbase"`:

`impute = "lin"` uses simple linear imputation to derive a value for an empty element in input vector `x` from its neighboring non-empty elements. This method is equivalent to the linear interpolation in the `profBinLin` method. Whether interpolation is performed if missing values are present at the beginning and end of `x` can be set with argument `noInterpolAtEnds`. By default interpolation is also performed at the ends interpolating from `0` at the beginning and towards `0` at the end. For `noInterpolAtEnds = TRUE` no interpolation is performed at both ends replacing the missing values at the beginning and/or the end of `x` with `0`.

`impute = "linbase"` uses linear interpolation to impute values for empty elements within a user-definable proximity to non-empty elements and setting the element's value to the `baseValue` otherwise. The default for the `baseValue` is half of the smallest value in `x` (`NA`s being removed). Whether linear interpolation based imputation is performed for a missing value depends on the `distance` argument. Interpolation is only performed if one of the next `distance` closest neighbors to the current empty element has a value other than `NA`. No interpolation takes place for `distance = 0`, while `distance = 1` means that the value for an empty element is interpolated from directly adjacent non-empty elements while, if the next neighbors of the current empty element are also `NA`, it's vale is set to `baseValue`. This corresponds to the linear interpolation performed by the `profBinLinBase` method. For more details see examples below.

### Value

A numeric vector with empty values imputed based on the selected `method`.

### Author(s)

Johannes Rainer

### Examples

    #######
    ## Impute missing values by linearly interpolating from neighboring
    ## non-empty elements
    x <- c(3, NA, 1, 2, NA, NA, 4, NA, NA, NA, 3, NA, NA, NA, NA, 2)
    imputeLinInterpol(x, method = "lin")
    ## visualize the interpolation:
    plot(x = 1:length(x), y = x)
    points(x = 1:length(x), y = imputeLinInterpol(x, method = "lin"), type = "l", col = "grey")

    ## If the first or last elements are NA, interpolation is performed from 0
    ## to the first non-empty element.
    x <- c(NA, 2, 1, 4, NA)
    imputeLinInterpol(x, method = "lin")
    ## visualize the interpolation:
    plot(x = 1:length(x), y = x)
    points(x = 1:length(x), y = imputeLinInterpol(x, method = "lin"), type = "l", col = "grey")

    ## If noInterpolAtEnds is TRUE no interpolation is performed at both ends
    imputeLinInterpol(x, method = "lin", noInterpolAtEnds = TRUE)

    ######
    ## method = "linbase"
    ## "linbase" performs imputation by interpolation for empty elements based on
    ## 'distance' adjacent non-empty elements, setting all remaining empty elements
    ## to the baseValue
    x <- c(3, NA, 1, 2, NA, NA, 4, NA, NA, NA, 3, NA, NA, NA, NA, 2)
    ## Setting distance = 0 skips imputation by linear interpolation
    imputeLinInterpol(x, method = "linbase", distance = 0)

    ## With distance = 1 for all empty elements next to a non-empty element the value
    ## is imputed by linear interpolation.
    xInt <- imputeLinInterpol(x, method = "linbase", distance = 1L)
    xInt

    plot(x = 1:length(x), y = x, ylim = c(0, max(x, na.rm = TRUE)))
    points(x = 1:length(x), y = xInt, type = "l", col = "grey")

    ## Setting distance = 2L would cause that for all empty elements for which the
    ## distance to the next non-empty element is <= 2 the value is imputed by
    ## linear interpolation:
    xInt <- imputeLinInterpol(x, method = "linbase", distance = 2L)
    xInt

    plot(x = 1:length(x), y = x, ylim = c(0, max(x, na.rm = TRUE)))
    points(x = 1:length(x), y = xInt, type = "l", col = "grey")

[Package xcms version 3.2.0 Index]