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FMM (version 0.4.1)

FMM-methods: Methods for objects of class 'FMM'

Description

The methods for objects of class 'FMM' are:

coefcoef method for S4 class 'FMM',
summarysummary method for S4 class 'FMM',
fittedfitted method for S4 class 'FMM',
residresid method for S4 class 'FMM'.

Usage

## S4 coef method for signature 'FMM'
coef(object,...)

## S4 summary method for signature 'FMM' summary(object,...)

## S4 fitted method for signature 'FMM' fitted(object,...)

## S4 resid method for signature 'FMM' resid(object,...)

Value

  • The function coef() returns a list with two components:

    MA numeric value. The estimated intercept parameter \(M\).
    waveA data.frame with the estimates of each FMM wave parameters. It is organised as one component per row.

  • The function summary() displays relevant results of the fitting. When it is assigned, this function returns a list with the following components:

    coefThe list returns by the function coef().
    peak.timeA data.frame with the estimates of the peak and trough times of each wave. It is organised as one component per row.
    residThe vector of residuals.
    R.squaredA numerical value with the R squared of each wave. The total R square is computed as the sum of the contribution of each component.

  • The function fitted() returns a data.frame with two columns: timePoints and fittedValues.

  • The function resid() returns a numeric vector with residuals of the model.

Arguments

object

object of class 'FMM'.

...

additional arguments passed to the method.

Examples

Run this code
## Generate example data:
fmm2.data <- generateFMM(0, rep(2, 2), c(1.5, 3.4), c(0.2, 2.3), c(0.1, 0.2),
                    plot = FALSE, outvalues = TRUE,
                    sigmaNoise = 0.5) # add a gaussian noise with sigma = 0.5

## Fit the FMM model with nback = 2 component
## fit is an object of S4 class 'FMM'
fit <- fitFMM(vData = fmm2.data$y,timePoints = fmm2.data$t,nback = 2,
              lengthAlphaGrid = 24,lengthOmegaGrid = 10)

## Extract coefficients of the model:
coef(fit)

## Summarize results:
summary(fit)

## Results on a list:
res <- summary(fit)
res$peak.time # fiducial points

## fitted values:
fit.values <- fitted(fit)

## residuals
res <- resid(fit)

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