Object returned from a call to getPeaklist.

- peaklist
A

`matrix`

with rows equal to the number of peak patterns used in fitting and five columns. For each row (pattern), the first column contains the initial position of the peak pattern (`loc_init`

, in Thomson), the second one contains the position of the most intense peak within a peak pattern (`loc_most_intense`

, in Thomson), the third one contains the charge state (`charge`

), the fourth one the quantification of the overall intensity of the pattern (`quant`

) and the last one contains the amplitude at the most intense peak (`amplitude`

).- peaklistprocessed
The result after applying the postprocessing procedure to the raw list

`peaklist`

. It is a matrix of the same structure as`peaklist`

, with two up to four additional columns: the fifth column contains the local noise level at the position, and the last one contains the ratio of the amplitude to local noise level (signal-to-noise ratio), hence quantitatively describing the significance of the peak pattern. If`goodnessoffit`

has been set to`TRUE`

, there are two additional columns labelled`goodness_of_fit`

and`ratio_adj`

. The column`goodness_of_fit`

contains a local assessment of the goodness-of-fit at the respective positions in the spectrum, while the column`ratio_adj`

contains a goodness-of-fit adjusted signal-to-noise ratio. If`postprocessed`

has been set to`FALSE`

when calling getPeaklist, this slot is an empty matrix.- model
One of "Gaussian" or "EMG".

- averagine.table
Averagine table used, cf.getPeaklist.

- loss
One of "L2" or "L1".

- alpha
Function for the parameter "alpha" (

`model = "EMG"`

).- sigma
Function for the parameter "sigma" (both models).

- mu
Function for the parameter "mu" (

`model = "EMG"`

).- charges
A

`numeric`

vector containing the set of charge states used.- basis
The matrix of basis functions if

`returnbasis`

has been set to`TRUE`

when calling getPeaklist. Otherwise, this slot is an empty matrix.- book
A

`matrix`

annotating each column of`basis`

. Each row corresponds to a template/peak pattern characterized by the initial position of the peak pattern (column`initial`

), the position of the most intense peak (column`most_intense`

) and the charge state (column`charge`

).- beta
A

`numeric`

vector storing the amplitudes for each peak pattern in`book`

/each column of`basis`

, obtained by non-negative least squares estimation (if`loss = "L2"`

) or by non-negative least absolute deviation estimation (if`loss = "L1"`

). Hence, together with`book`

,`cbind(book, beta)`

constitutes a predecessor of`peaklist`

.- locnoise
A

`matrix`

of local quantiles of the intensities computed along the spectrum. Each row corresponds to a m/z value of the spectrum (ordered increasingly), and each column to a quantile as indicated by the column names. For instance,`slot(object, "locnoise")[,"0.5"]`

would give the vector of local medians.- noiselevel
A

`numeric`

vector storing the noise level used for computation of the signal-to-noise ratios appearing in`peaklistprocessed`

.- goodnessoffit
A

`numeric`

vector storing the local goodness-of-fit criterion. An empty vector unless`control.postprocessing$goodnessfittrue`

was`TRUE`

when`getPeaklist`

was called.- data
A

`list`

storing the spectrum used to generate the object.

- show
Use

`show(object)`

for brief information about the object.- threshold
Only applicable if

`postprocessed`

has been set to`TRUE`

when calling`getPeaklist`

. A function to threshold`peaklistprocessed`

, yielding a peaklist maintaining only those peaks exceeding a specified threshold. Optionally, re-fitting of the spectrum using only those templates that have passed the thresholding step can be performed. The argument list is given by`object`

An object of class

`peaklist`

.`threshold`

The value to be used as threshold.

`ratio`

Whether to use the signal-to-noise ratio

`"ratio"`

or the goodness-of-fit adjusted signal-to-noise ratio`"ratio_adj"`

`refit`

Whether re-fitting of the spectrum should be done, using only the templates above the threshold.

`trace`

A

`logical`

indicating whether information tracing the different steps of the fitting process should be displayed. Only used if`refit = TRUE`

.`eps`

Function values below

`eps`

are set equal to precisely zero in order to make the basis function matrix sparse. Only used if`refit = TRUE`

.

.

- visualize
A function to displaying the results of the fitting procedure, in particular significant peak patterns, in selected m/z ranges. The description of the arguments is as follows:

`object`

An object of class

`peaklist`

.`mz`

The vector of m/z values used to obtain

`object`

.`intensities`

The vector of intensities used to obtain

`object`

.`lower, upper`

The m/z range for which the result of the fitting procedure should be visualized (

`lower < upper`

).*Hint*: the difference`upper - lower`

should be between 0-30. If it is significantly larger, computation times increase considerably. Moreover, this will lead to a reduced quality of the plot.`truth`

May be set to

`TRUE`

if one has a precise knowledge of the true underlying signal (normally only occuring for simulated data) and one wants to compare the results with the gold standard. If`truth = TRUE`

,`booktrue`

(s. below) has to be specified. In this case, the true signal is displayed as upper panel in the plot.`signal`

A

`logical`

indicating whether the raw spectrum in the range`[lower,upper]`

should be plotted. If`TRUE`

, it is displayed as upper panel or as one of the middle panels.`fitted`

A

`logical`

indicating whether basically all (with restrictions, s.`cutoff.functions`

and`cutoff.eps`

below) fitted templates should be plotted. If`TRUE`

, the result is displayed as a middle panel or as lower panel.`postprocessed`

A

`logical`

indicating whether fitted templates after postprocessing should be plotted. If`TRUE`

, the result is displayed as lower panel.`fittedfunction`

A

`logical`

indicating whether the fitted function should be drawn as lines in the panel displaying the raw spectrum (requires`signal = TRUE`

). Note that the fitted function is the result of summing up all fitted templates multiplied by their amplitude. Setting`fittedfunction = TRUE`

requires that`object`

contains the matrix of basis functions.`fittedfunction.cut`

A

`logical`

indicating whether the fitted function after cutting peak patterns falling below a prespecified cutoff should be drawn as lines in the panel displaying the raw spectrum (requires`signal = TRUE`

). Setting`fittedfunction.cut = TRUE`

requires that`object`

contains the matrix of basis functions.`quantile`

Optional argument. If

`quantile`

is specified, it has to be one of the values`0.1,...,0.9`

, and the corresponding local quantile as contained in the slot`locnoise`

(s. above) will be added to the plot as dotted line.`booktrue`

Required if and only if

`truth = TRUE`

. In this case,`booktrue`

has to be a matrix having the same structure as`cbind(slot(object, "book"), slot(object, "beta"))`

, i.e. the first two columns of`booktrue`

contain initial- and most intense peak locations within a peak pattern, the third column contains the charge state and the fourth one the amplitude of the most intense peak.*Note:*the 'truth' is computed according to`slot(object, model)`

. This excludes the following scenario: assuming that the true peak shapes is`"EMG"`

, but the chosen model is`"Gaussian"`

. Then the true model in this function is computed according to the latter model.`cutoff.eps, cutoff.functions`

Control arguments reducing the number of templates to be plotted if

`fitted = TRUE`

. Specifying`cutoff.eps`

removes all templates with intensity smaller than`cutoff.eps`

. Specifying`cutoff.functions`

as a positive integer only plots the`cutoff`

'most intense' templates.`...`

Additional options passed to

`plot`

.

Note that the colours in the plot have no meaning. They are only used to distinguish between different patterns within a panel. Further note that the colour of a pattern appearing in several panels may vary from panel to panel.

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