Uses a series of C functions to calculate the derivative of the objectiveICA function. Offers a choice between the Huber substitution function or the logCosh function.

1 | ```
gradientICA(T, E, N, C, PH, method = c("Huber", "Cosh"))
``` |

`T` |
Vector of angles of length p |

`E` |
Financial time series data of dimension nxd |

`N` |
Vector of lags that MUST be arranged in ascending order |

`C` |
Real number C which is used for Huber substitution or Logcosh substitution |

`PH` |
Phi matrix of weights of dimension q*q |

`method` |
Choice between use of Huber or logCosh substitution methods |

More details to help above

Gradient of objective value

Erjie Ang ea75@cornell.edu

See

1 2 3 4 5 6 7 8 9 10 11 12 |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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