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quantilogram

The goal of quantilogram is to measure nonlinear dependence between two variables, based on either unconditional or conditional quantile functions.

Installation

You can install the released version of quantilogram from CRAN with:

install.packages("quantilogram")

Example

This is a basic example which shows you how to solve a common problem:

library(quantilogram)
## basic example code

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Version

Install

install.packages('quantilogram')

Monthly Downloads

220

Version

2.0.1

License

GPL-3

Maintainer

Tatsushi Oka

Last Published

May 31st, 2020

Functions in quantilogram (2.0.1)

crossqreg.max.partial

Partial Corss-Quantilogram upto a given lag order
crossqreg.max

Corss-Quantilogram up to a Given Lag Order
crossqreg

Cross-Quantilogram
qreg.hit

Quantile Hit
quantilogram-package

quantilogram: Cross-Quantilogram
crossqreg.partial

Paritial Cross-Quantilogram
crossq.partial

Paritial Cross-Quantilogram
crossqreg.sb

Stationary Bootstrap for the Cross-Quantilogram
q.hit

Quantile Hit
crossq.partial.sb

Stationary Bootstrap for the Partial Cross-Quantilogram
crossq.partial.sb.opt

Stationary Bootstrap for the Partial Cross-Quantilogram dwith the choice of the stationary-bootstrap parameter
crossq.sb.opt

Stationary Bootstrap for the Cross-Quantilogram with the choice of the stationary-bootstrap parameter
crossq.sb

Stationary Bootstrap for the Cross-Quantilogram
sys.risk

The Data Set for Systemic Risk Analysis
sb.index

Stationary Bootstrap Index
stock

The Data Set of Monthly Stock Return and Sotck Variance
crossq.max

Corss-Quantilogram up to a Given Lag Order
corr.lag.partial

Partial Cross-correlation function
Qstat.reg.sb

Stationary Bootstrap for Q statistics
crossq.max.partial

Partial Corss-Quantilogram upto a given lag order
corr.lag

Correlation Function
crossq

Cross-Quantilogram
Qstat

Q-statistics
Qstat.sb

Stationary Bootstrap for Q statistics
Qstat.sb.opt

Stationary Bootstrap for Q statistics