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bvar1

low level estimation of a bayesian VAR model

CALLING SEQUENCE

rbvar=bvar1(nlag,tight,weight,decay,y,x)

PARAMETERS

Input

* nlag = the lag length of the VAR

* tight = Litterman's tightness hyperparameter

* weight = Litterman's weight (matrix or scalar)

* decay = Litterman's lag decay = lag^(-decay)

* y = (nobs x neqs) matrix of endogenous variables

* x = (nobs x nx) matrix of exogenous variables (optional)

 

Output

* rbvar = a results tlist with:

  . rbvar('meth')  = 'bvar'

  . rbvar('y')     = y data vector

  . rbvar('x')     = x data matrix

  . rbvar('nvar')  = # exogenous variables

  . rbvar('nobs')  = # observations

  . rbvar('neqs')  = # endogenous variables

  . rbvar('nlag')  = # lags

  . rbvar('tight')  = Litterman's tightness hyperparameter

  . rbvar('weight')  = Litterman's weight (matrix or scalar)

  . rbvar('decay')  = Litterman's lag decay = lag^(-decay)

  . rbvar('beta')  = bhat, with rbvar('beta')(:,i): coefficients for equation # i

  . rbvar('tstat') = t-stats, with rbvar('tstat')(:,i): t-stat for equation # i

  . rbvar('pvalue')= pvalue of the betas, with rbvar('pvalue')(:,i): p-value for equation # i

  . rbvar('resid') = residuals, with rbvar('resid')(:,i): residuals for equation # i

  . rbvar('yhat') = yhat, with rbvar('yhat')(:,i): residuals for equation # i

  . rbvar('sige')  = estimated variances rbvar('sige')(i): variance for equation # i

  . rbvar('ser')   = standard errors of the regression with rbvar('ser')(i): standard error for equation # i

  . rbvar('dw')    = Durbin-Watson Statistic, with: rbvar('dw')(i): DW for equation # i

  . rbvar('rsqr')  = rsquared, with rbvar('rsqr')(i) : rsquared for equation # i

  . rbvar('rbar')  = rbar-squared

  . rbvar('sigma') = (neqs x neqs) var-covar matrix of the regression

  . rbvar('nx') = # exogenous variables

  . rbvar('prescte') = boolean indicating the presence or absence of a constant in the regression

  . rbvar('xpxi)   = inv(x'*x)

DESCRIPTION

Estimates a bayesian VAR of order p. Applies when the variables are already in matrix form. Does note display any result on screen (see bvar for a more complete function).

EXAMPLE

load(GROCERDIR+'/data/datajpl.dat') // load Le Sage matlab data
y=explone(list('illinos','indiana','kentucky','michigan','ohio','pennsyvlania','tennesse','westvirginia'))
// stores the data into matrix y
rbvar = bvar1(2,0.1,1,0.5,y)
// This function should be mainly be used in other functions.

AUTHOR

Eric Dubois 2002

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