fit_gaussians {PrInCE} | R Documentation

## Fit a mixture of Gaussians to a chromatogram curve

### Description

Fit mixtures of one or more Gaussians to the curve formed by a chromatogram profile, using nonlinear least-squares.

### Usage

    fit_gaussians(
      chromatogram,
      n_gaussians,
      max_iterations = 10,
      min_R_squared = 0.5,
      method = c("guess", "random"),
      filter_gaussians_center = TRUE,
      filter_gaussians_height = 0.15,
      filter_gaussians_variance_min = 0.1,
      filter_gaussians_variance_max = 50
    )

### Arguments

`chromatogram` | a numeric vector corresponding to the chromatogram trace
`n_gaussians` | the number of Gaussians to fit
`max_iterations` | the number of times to try fitting the curve with different initial conditions; defaults to 10
`min_R_squared` | the minimum R-squared value to accept when fitting the curve with different initial conditions; defaults to 0.5
`method` | the method used to select the initial conditions for nonlinear least squares optimization (one of "guess" or "random"); see `make_initial_conditions` for details
`filter_gaussians_center` | true or false: filter Gaussians whose centres fall outside the bounds of the chromatogram
`filter_gaussians_height` | Gaussians whose heights are below this fraction of the chromatogram height will be filtered. Setting this value to zero disables height-based filtering of fit Gaussians
`filter_gaussians_variance_min` | Gaussians whose variance falls below this number of fractions will be filtered. Setting this value to zero disables filtering.
`filter_gaussians_variance_max` | Gaussians whose variance is above this number of fractions will be filtered. Setting this value to zero disables filtering.

### Value

a list with six entries: the number of Gaussians used to fit the curve; the R^2 of the fit; the number of iterations used to fit the curve with different initial conditions; the coefficients of the fit model; and the fit curve predicted by the fit model.

### Examples

    data(scott)
    chrom <- clean_profile(scott[1, ])
    fit <- fit_gaussians(chrom, n_gaussians = 1)

[Package PrInCE version 1.10.0 Index]