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