computes Schmidt-Phillips test
[resulsp]=schmiphi(namey,t,varargin)
* 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
* 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
load(GROCERDIR+'/data/bdhenderic.dat'); bounds('1964q3','1989q2'); 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. | ![]() | ![]() |