ConcNoiseModel-class. chemosensors 0.7.7

Usage

defaultParConcNoiseModel()

ConcNoiseModel(...)

Arguments

...: parameters of constructor.

Value

List of the default parameters.

Description

Method logf.

Class ConcNoiseModel emulates perturbations in the analyte delivery system. The noise term is a normally distributed noise with zero-mean and diagonal covariance matrix. The diagonal structure of the covariance matrix underlines that the concentration noises of analytes do not affect each other.

Get default constructor parameters of class ConcNoiseModel.

Constructor method of ConcNoiseModel Class.

Wrapper function ConcNoiseModel.

Details

Slots of the class:

`gases`	Gas indices.
`ngases`	The number of gases.
`gnames`	Names of gases.
`concUnits`	Concentration units external to the model, values given in an input concentration matrix.
`concUnitsInt`	Concentration units internal for the model, values used to induce the noise.
`csd`	Parameter of standard deviation used to generate the noise. The deault value is 0.1.
`cntype`	Noise type (`logconc`).
`cnlogf`	Scaling factor for for log-terms if the noise type is `logconc`. The default value is `c(1, 1, 2)`.

The logarithm term expresses an additional scaling of the amplitude applied to simulate more noise on high levels of concentration.

Methods of the class:

`predict`	Generates noise into the columns of an input concentration matrix.
`csd`	Gets the noise level.
`csd<-`	Sets the noise level.

The plot method has one type (parameter y):

noise Depicts the noise vectors generated by the model.

Examples

# model: default initialization
cn <- ConcNoiseModel()

# get information about the model
show(cn)

 Concentration Noise Model (csd 0.1), noise type 'logconc'

print(cn)

 Concentration Noise Model
 - 3 gases A, B, C 
 - csd: 0.1 
 - noise type: logconc 
 - log-factor: 1, 1, 2 


plot(cn)  



# model: custom parameters
# - many sensors
cn <- ConcNoiseModel(csd=0.5, gases=c(1, 3))

print(cn)

 Concentration Noise Model
 - 2 gases A, C 
 - csd: 0.5 
 - noise type: logconc 
 - log-factor: 1, 2 


plot(cn)



# method plot
#  - plot types 'y': noise
cn <- ConcNoiseModel() # default model

plot(cn, "noise", main="plot(cn, 'noise')") 


# default plot type, i.e. 'plot(cn)' does the same plotting