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micss (version 0.2.0)

Modified Iterative Cumulative Sum of Squares Algorithm

Description

Companion package of Carrion-i-Silvestre & Sansó (2023): "Generalized Extreme Value Approximation to the CUMSUMQ Test for Constant Unconditional Variance in Heavy-Tailed Time Series". It implements the Modified Iterative Cumulative Sum of Squares Algorithm, which is an extension of the Iterative Cumulative Sum of Squares (ICSS) Algorithm of Inclan and Tiao (1994), and it checks for changes in the unconditional variance of a time series controlling for the tail index of the underlying distribution. The fourth order moment is estimated non-parametrically to avoid the size problems when the innovations are non-Gaussian (see, Sansó et al., 2004). Critical values and p-values are generated using a Generalized Extreme Value distribution approach. References Carrion-i-Silvestre J.J & Sansó A (2023) . Inclan C & Tiao G.C (1994) , Sansó A & Aragó V & Carrion-i-Silvestre J.L (2004) .

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Version

Install

install.packages('micss')

Monthly Downloads

167

Version

0.2.0

License

GPL-2

Maintainer

Andreu Sansó

Last Published

August 22nd, 2024

Functions in micss (0.2.0)

p.val.kappa

P-values
plot.icss

plot.icss
lrv.spc.bartlett

lrv.spc.bartlett
micss

Modiffied Iterative Cumulative Sum of Squares Algorithm
step3

step3
step2a

step2a
taula.icss

taula.icss
taula.micss

taula.micss
steps1.to.2b

steps1.to.2b
sr_shape

sr_shape
var.est.icss

var.est.icss
whitening

Whitening
logReturnsRandDollar

Data used in the examples
kappa_test

CUMSUMQ test to test for changes in the unconditional variance
alpha_hill

Hill's estimator of the tail index
alpha_nr

Nicolau & Rodrigues estimator of the tail index
icss

Iterative Cumulative Sum of Squares Algorithm
print.icss

print.icss
cv.kappa

Critical Values
estimate.alpha

estimate.alpha
data

Data used in the examples
sr_scale

sr_scale
sr_loc

sr_loc
step2b

step2b
step2c

step2c
print.micss

print.micss