SlidingWindows (version 0.2.0)

descritive.SlidingWindows: Descritive statistics with sliding windows.

Description

This function generates descriptive statistics of a univariate time series with sliding windows approach.

Usage

descritive.SlidingWindows(y, w = 99, skewness = "moment", kurtosis = "moment")

Arguments

y

A vector containing univariate time series.

w

An integer value indicating the window size \(w < length(y)\). If \(w = length(y)\), will be computed the function will not slide.

skewness

A non-numeric value. See PerformanceAnalytics package.

kurtosis

A non-numeric value. See PerformanceAnalytics package.

Value

A list containing "w", "min","max","mean", "median", "standard deviation","skewness" and "kurtosis".

Details

This function include following measures: min, max, mean, median, standard deviation, skewness and kurtosis.

References

Guedes, E.F. Modelo computacional para an<U+00E1>lise de movimentos e co-movimentos de mercados financeiros, Ph.D. thesis, Programa de P<U+00F3>s-gradua<U+00E7><U+00E3>o em Modelagem Computacional e Tecnologia Industrial. Centro Universit<U+00E1>rio Senai Cimatec, 2019.

Examples

# NOT RUN {
y <- rnorm(100)
descritive.SlidingWindows(y, w=99, skewness="moment", kurtosis="moment")

# }