descritive.SlidingWindows: Descritive statistics with sliding windows.

In SlidingWindows: Methods for Time Series Analysis

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.

Details

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

Value

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

References

Guedes, E.F. Modelo computacional para análise de movimentos e co-movimentos de mercados financeiros, Ph.D. thesis, Programa de Pós-graduação em Modelagem Computacional e Tecnologia Industrial. Centro Universitário Senai Cimatec, 2019.

Examples

y <- rnorm(100)
descritive.SlidingWindows(y, w=99, skewness="moment", kurtosis="moment")

SlidingWindows documentation built on April 11, 2021, 9:07 a.m.