Description Usage Arguments Details Value Examples

Computes running covariance between time-series `x`

and short-time pattern `y`

.

1 | ```
RunningCov(x, y, circular = FALSE)
``` |

`x` |
A numeric vector. |

`y` |
A numeric vector, of equal or shorter length than |

`circular` |
Logical; whether running variance is computed assuming
circular nature of |

Computes running covariance between time-series `x`

and short-time pattern `y`

.

The length of output vector equals the length of `x`

.
Parameter `circular`

determines whether `x`

time-series is assumed to have a circular nature.
Assume *l_x* is the length of time-series `x`

, *l_y* is the length of short-time pattern `y`

.

If `circular`

equals `TRUE`

then

first element of the output vector corresponds to sample covariance between

`x[1:l_y]`

and`y`

,last element of the output vector corresponds to sample covariance between

`c(x[l_x], x[1:(l_y - 1)])`

and`y`

.

If `circular`

equals `FALSE`

then

first element of the output vector corresponds to sample covariance between

`x[1:l_y]`

and`y`

,the

*l_x - W + 1*-th last element of the output vector corresponds to sample covariance between`x[(l_x - l_y + 1):l_x]`

,last

`W-1`

elements of the output vector are filled with`NA`

.

See `runstats.demo(func.name = "RunningCov")`

for a detailed presentation.

A numeric vector.

1 2 3 4 5 |

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