Description Usage Arguments Details Value Author(s) See Also

This `selfStart`

model evalueates the Gaussian model and its
gradient. It has an `initial`

attribute that will evalueate
the inital estimates of the parameters `mu`

, `sigma`

,
and `h`

.

1 |

`x` |
a numeric vector of values at which to evaluate the model |

`mu` |
mean of the distribution function |

`sigma` |
standard deviation of the distribution fuction |

`h` |
height of the distribution function |

Initial values for `mu`

and `h`

are chosen from the
maximal value of `x`

. The initial value for `sigma`

is
determined from the area under `x`

divided by `h*sqrt(2*pi)`

.

A numeric vector of the same length as `x`

. It is the value
of the expression `h*exp(-(x-mu)^2/(2*sigma^2)`

, which is a
modified gaussian function where the maximum height is treated
as a separate parameter not dependent on `sigma`

. If arguments
`mu`

, `sigma`

, and `h`

are names of objects, the
gradient matrix with respect to these names is attached as an
attribute named `gradient`

.

Colin A. Smith, [email protected]

xcms documentation built on May 18, 2019, 2 a.m.

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