supmz: Detecting Structural Change with Heteroskedasticity

In SupMZ: Detecting Structural Change with Heteroskedasticity

Description

Calculates the sup MZ value to detect the unknown structural break points under Heteroskedasticity

Usage

supmz(formula, data, nBoot = 100)

## Default S3 method:
supmz(formula, data, nBoot = 100)

Arguments

formula	Formula for the linear model to be used. It may contain any number of independent variables.
data	Data frame containing dependent and independent variables.
nBoot	Number of bootstrap samples to compute the critical region.

Value

MZ Gives values of MZ as given by Mumtaz et.al (2017)

BreakLocation Provides the data point position where the structural break occured

SupMzValue Returns the supremum value from MZ values

SupMZ0 Returns the bootstrapped critical value for testing the significance of SupMZ

nBoot Shows the number of bootstrap samples used to compute the critical region

Author(s)

1. Muhammad Yaseen ([e-mail])

2. Sami Ullah ([e-mail])

3. Gulfam Haider ([e-mail])

References

Mumtaz Ahmed, Gulfam Haider & Asad Zaman (2017). Detecting structural change with heteroskedasticity. Communications in Statistics - Theory and Methods. 46(21):10446-10455, DOI: 10.1080/03610926.2016.1235200

Examples

data(Japan)
fm1 <- supmz(formula = C~Y, data = Japan, nBoot = 10)
fm1

data(Belgium)
fm2 <- supmz(formula = C~Y, data = Belgium, nBoot = 10)
fm2

data(Srilanka)
fm3 <- supmz(formula = C~Y, data = Srilanka, nBoot = 10)
fm3

SupMZ documentation built on Jan. 16, 2020, 5:05 p.m.