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cusumf

forward cusum stability tests

CALLING SEQUENCE

[rcusum]=cusumf(y,arg1,...,argn)

PARAMETERS

Input

* y = a time series, a real (nx1) vector or a string equal to the name of a time series or a (nx1) real vector between quotes

* argi = an argument that can be:

  - a time series

  - a real (nx1) vector

  - a string equal to the name of a time series or a (nx1) real vector between quotes

  - the string 'noprint' if the user doesn't want to print the results of the regression

  - the string 'size=x' where x=0.01, 0.05 or 0.1 is the size chosen for the teste (default =0.05)

  - 'dropna' if the user wants to remove the NA values from the data

 

Output

* rcusum = a results tlist with:

  - rcusum('meth')='cusum'

  - rcusum('nobs')= # of observations

  - rcusum('nvar')= # of variables

  - rcusum('y')= y data vector

  - rcusum('x')= x matrix vector

  - rcusum('rres')= vector of recursive residuals

  - rcusum('cusum')= cusum test

  - rcusum('cusum_l90')= the lower value of its 90% confidence interval

  - rcusum('cusum_u90')= the upper value of its 90% confidence interval

  - rcusum('cusum_l95')= the lower value of its 95% confidence interval

  - rcusum('cusum_u95')= the upper value of its 95% confidence interval

  - rcusum('cusum_l99')= the lower value of the 99% confidence interval

  - rcusum('cusum_u99')= the upper value of the 99% confidence interval

  - rcusum('cusums')= squared cusum test

  - rcusum('cusums_l90')= the lower value of its 90% confidence interval

  - rcusum('cusums_u90')= the upper value of its 90% confidence interval

  - rcusum('cusums_l95')= the lower value of its 95% confidence interval

  - rcusum('cusums_u95')= the upper value of its 95% confidence interval

  - rcusum('cusums_l99')= the lower value of the 99% confidence interval

  - rcusum('cusums_u99')= the upper value of the 99% confidence interval

  - rcusum('prests')=boolean indicating the presence or absence of a time series in the regression

  - rcusum('namey') = name of the y variable

  - rcusum('namex') = name of the x variables

  - rcusum('bounds') = if there is a timeseries in the regression, the bounds of the test (which are the bounds of the regression, less the k first dates)

  - rcusum('dropna') = boolean indicating if NAs have been droped

  - rcusum('nonna') = vector indicating position of non-NAs (if the option 'dropna' was active)

DESCRIPTION

Computes forward cusum and cusum-squares test and plots the tests values along with their 5% confidence bands (see Brown R.L, J. Durbin and J.M Evans (1975):"Techniques for Testing the Constancy of Regression Relationship over Time", Journal of the Royal Statistical Society, Series B, 2, 149-192).

EXAMPLE

load(GROCERDIR+'/macros/grocer/db/bdhenderic.dat') ;
bounds('1964q3','1985q2') ;
r=cusumf('delts(lm1-lp)','delts(lp)','delts(lagts(1,lm1-lp-ly))','rnet','lagts(1,lm1-lp-ly)','cte')
 
// Example taken from function cusum_d. The example provides the cusum forward stability test for the estimation of Hendry and Ericsson equation # 6.

AUTHOR

Eric Dubois 2002-2007

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