# coronoid: Ridge Estimation by Modified Corona Method In Rwave: Time-Frequency Analysis of 1-D Signals

## Description

Estimate a ridge using the modified corona method (modified cost function).

## Usage

 ```1 2 3``` ```coronoid(tfrep, guess, tfspec=numeric(dim(tfrep)), subrate=1, temprate=3, mu=1, lambda=2 * mu, iteration=1000000, seed=-7, stagnant=20000, costsub=1, plot=TRUE) ```

## Arguments

 `tfrep` Estimate for the contribution of the noise to modulus. `guess` Initial guess for the algorithm. `tfspec` Estimate for the contribution of the noise to modulus. `subrate` Subsampling rate for ridge estimation. `temprate` Initial value of temperature parameter. `mu` Coefficient of the ridge's derivative in cost function. `lambda` Coefficient of the ridge's second derivative in cost function. `iteration` Maximal number of moves. `seed` Initialization of random number generator. `stagnant` Maximum number of stationary iterations before stopping. `costsub` Subsampling of cost function in output. `plot` When set(default), some results will be shown on the display.

## Details

To accelerate convergence, it is useful to preprocess modulus before running annealing method. Such a preprocessing (smoothing and subsampling of modulus) is implemented in `coronoid`. The parameter subrate specifies the subsampling rate.

## Value

Returns the estimated ridge and the cost function.

 `ridge` 1D array (of same length as the signal) containing the ridge. `cost` 1D array containing the cost function.

## Warning

The returned cost may be a large array. The argument costsub allows subsampling the cost function.

## References

See discussion in text of “Practical Time-Frequency Analysis”.

## See Also

`corona`, `icm`, `snake`, `snakoid`.

Rwave documentation built on May 2, 2019, 9:15 a.m.