let us consider following matlab code
help aicbic aicbic Akaike and Bayesian information criteria Syntax: [aic,bic] = aicbic(logL,numParam,numObs) Description: Given optimized log-likelihood function values logL obtained by fitting a model to data, compute the Akaike (AIC) and Bayesian (BIC) information criteria. Since information criteria penalize models with additional parameters, aic and bic select models based on both goodness of fit and parsimony. When using either AIC or BIC, models that minimize the criteria are preferred. Input Arguments: logL - Vector of optimized log-likelihood objective function values associated with parameter estimates of various models. numParam - Number of estimated parameters associated with each value in logL. numParam may be a scalar applied to all values in logL, or a vector the same length as logL. All elements of numParam must be positive integers. Optional Input Argument: numObs - Sample sizes of the observed data associated with each value of logL. numObs is required for computing BIC, but not AIC. numObs may be a scalar applied to all values in logL, or a vector the same length as logL. All elements numObs must be positive integers. Output Arguments: aic - Vector of AIC statistics associated with each logL objective function value. The AIC statistic is defined as: aic = -2*logL + 2*numParam bic - Vector of BIC statistics associated with each logL objective function value. The BIC statistic is defined as: bic = -2*logL + numParam*log(numObs)
Let us suppose that we have the data in a
How do I apply this matlab function (
I am trying to find the AR order of the data.