rolling: Rolling aggregate functions

In kaldhusdal/temporal:

Description

Functions for calculating different rolling aggregates.

Usage

rolling.sum(x, w, type = "lag", na.rm = FALSE)

Arguments

x	An atomic vector of class numeric.
w	An integer value specifying the width of the windows over which to calculate the rolling aggregate.
type	Either one of "lag" (window ends with current observation), "mid" (current observation is in the middle of the window) or "lead" (window starts with current observation).
na.rm	A logical value indicating whether NA values should be ignored when calculating the rolling aggregates.

Details

• If na.rm is set to TRUE and there are no valid values inside a window, rolling.sum will return the value 0.

• rolling.var returns the unbiased sample estimator Var(x) = (1 / (n - 1)) * sum_i (x_i - mu)^2.

• rolling.sd simply calls rolling.var and returnes the square root of the rolling variances.

• The skewness measures the direction and degree of a distrubution's asymmetry. A symmetric distribution has a skewness of zero, while a "left-skewed" (or "left-tailed") distribution (where the arithmetic mean is less than the median) has a negative skewness. The Fisher-Pearson standardised moment coefficient, as discussed by Joanes and Gill (1998) is used to calculate the rolling skewness:

  (sqrt(n(n - 1))/(n(n - 2)) ((sum_i (x_i - mu)^3)/((1 / n) sum_i (x_i - mu)^2)^(3 / 2))

• The kurtosis describes the "tailedness" of a distribution. Using s2 = sum_i (x_i - mu)^2, s4 = sum_i (x_i - mu)^4 and Var(x) = s2 / (n - 1), the kurtosis is defined as follows:

  kurtosis = (n(n - 1) / ((n - 1)(n - 2)(n - 3))) (s4 / Var(x)^2) - 3(((n - 1)^2 / ((n - 2)(n - 3)))).

  The formula is can be found in Sheskin (2000) and yields an expected kurtosis of zero for a Gaussian distribution.

References

Sheskin, D.J. (2000) Handbook of Parametric and Nonparametric Statistical Procedures, Second Edition. Boca Raton, Florida: Chapman & Hall/CRC.

Joanes, D. N. and Gill, C. A. (1998), Comparing measures of sample skewness and kurtosis. Journal of the Royal Statistical Society: Series D (The Statistician), 47: 183-189. doi:10.1111/1467-9884.00122

Examples

x <- rnorm(100)
rolling.sum(x = x, w = 10)

kaldhusdal/temporal documentation built on Nov. 24, 2019, 11:19 p.m.