Grocer Function
NAME
schmiphi - computes Schmidt-Phillips test
CALLING SEQUENCE
[resulsp]=schmiphi(namey,t,varargin)
PARAMETERS
Input
-
namey
: 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
-
t
: order of time polynomial in the null-hypothesis
- t = 0, for constant term
- t = 1, for constant plus time-trend
- t = 2,3 or 4 for higher order time trend polynomial
Output
-
result : results tlist with:
- result('meth') = 'schmiphi'
- result('namey') = name of the tested variable
- result('y') = (nobsx1) vector of endogenous variables
- result('namey') = name of the tested variable
- result('nobs') = # of observations
- result('t') = order of the polynomial trend
- result('lag(NW)') = # of lags of the Newey-West window
- result('phi') = value of the phi test
- result('rho') = rho statistics
- result('tau') = tau statisctics
- result('v_rho_1%') = critical value of the rho-test at the 1% level
- result('v_rho_5%') = critical value of the rho-test at the 5% level
- result('v_rho_10%') = critical value of the rho-test at the 10% level
- result('v_tau_1%') = critical value of the tau-test at the 1% level
- result('v_tau_5%') = critical value of the tau-test at the 5% level
- result('v_tau_10%') = critical value of the tau-test at the 10% level
- result('prests') = boolean indicating the presence or absence of a time series in the regression
- result('bounds') = if there is a timeseries in the regression, the bounds of the regression
DESCRIPTION
Computes Schmidt-Phillips test.
EXAMPLE
r=schmiphi('lm1',1)
Example taken from function schmiphi_d. Tests if variable lm1 from data base hendryericsson() is
trend stationary or has a unit root.
AUTHOR
Eric Dubois 2002